Careers at SentraAI
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Solutions Architect (Data / AI)
- Location: Abu Dhabi, United Arab Emirates - Employment type: Full time, permanent - Experience: Seven years or more in data or software engineering, with at least two leading delivery teams on client sites. - Reports to: Chief Technology Officer ## Job Summary As the Solutions Architect (Data / AI) at SentraAI you will own the technical design across data platforms, agent architecture, integrations and governance for client engagements. You will be accountable for decisions that balance speed, cost and maintainability, and for defending the design to client architects. You will lead a small onsite delivery team, run client governance forums, translate loose scope into defined deliverables and acceptance criteria, protect engagements from scope drift, and own knowledge transfer and handover to the client. You will also support pre sales on scoping and estimation for engagements you may lead. ## About SentraAI SentraAI is a specialist enterprise AI firm, focused on helping large, regulated organisations move AI and data platforms from experimentation into production safely and sustainably. We work inside enterprise run-states, where governance, operational risk, change control, and long-term ownership are integral to delivery. Our teams are trusted to design and deliver systems, platforms, and operating models that can be run, audited, and evolved, not just launched. We prioritise engineering discipline, architectural clarity, and delivery quality over speed theatre or hype. ## Key Responsibilities ### Solution ownership - Own end to end solution design across data platform, LLM/agent architecture, integrations and governance - Make and document trade-off decisions between speed, cost and maintainability - Ensure security, data residency and audit requirements are designed in ### Delivery leadership and governance - Lead and allocate work across a team of two to four onsite engineers and hold the quality line on deliverables - Run client governance forums from daily stand ups to quarterly reviews and keep status honest - Protect the engagement from scope drift and raise commercial change through SentraAI leadership early ### Handover, knowledge transfer and pre sales - Own knowledge transfer from week one including documentation, runbooks, training and shadowing - Convert loose scope into defined deliverables, acceptance criteria and a plan with real dependencies - Support pre sales on scoping and estimation for engagements you would lead ### Also in the role - Own the solution design across data platform, agent architecture, integration and governance, and defend it to client architects - Lead a team of two to four engineers onsite, allocating work and holding the quality line on what we deliver - Run the client governance forums, from daily stand ups to the quarterly review, and keep the status honest - Own knowledge transfer as a deliverable from week one, documentation, runbooks, training, shadowing - Support pre sales on scoping and estimation for engagements you would go on to lead ## Required Qualifications ### Essential - Seven years or more in data or software engineering - At least two examples leading delivery teams on client sites - Track record of taking an enterprise system from design to production and handing it over successfully - Able to hold a room of senior client stakeholders, including when the news is bad - Experience in regulated environments where security, data residency and audit are design inputs ### Technical competence - Deep experience in modern data platforms or production LLM and agent systems - Databricks experience preferred - Working competence in the complementary area (data platform or LLM/agent systems) - Hands on enough to review the team’s work and unblock it ### Also required - Convert loose scope into defined deliverables, acceptance criteria and a plan with real dependencies in it - Make the calls on trade offs between speed, cost and maintainability, and record why - Seven years or more in data or software engineering, with at least two leading delivery teams on client sites - Deep experience in either modern data platforms, Databricks preferred, or production LLM and agent systems, and working competence in the other - Experience in regulated environments, with security, data residency and audit treated as design inputs - Hands on enough to review the team's work properly and unblock it ## Advantageous but Not Mandatory - Databricks certifications or demonstrable Databricks project experience - Direct production experience with LLMs, agents or orchestration systems - Experience of working in regulated sectors such as finance, healthcare or government ## Why Work for SentraAI Enterprise AI, done properly. We exist to take AI and data out of experimentation and into production environments that are regulated, scrutinised, and expected to work every day. Quality is not optional. SentraAI is built on the belief that engineering discipline, governance by design, and delivery rigour are competitive advantages, not overhead. Clear ownership and accountability. You will be trusted with real responsibility, clear mandates, and meaningful outcomes, not diluted roles or performative activity. Work that survives contact with reality. We design systems, operating models, and decisions that still stand up months and years after go-live, not just at demo time. Run-state matters as much as build-state. We optimise for operability, auditability, and change control from day one, because that is where enterprise value is won or lost. Substance over hype. We deliberately avoid delivery theatre, buzzwords, and novelty for novelty sake. Credibility is earned through execution. Learn from experienced practitioners. You will work alongside people who have built, broken, fixed, and run enterprise systems, and who care deeply about doing the work properly. A firm with a point of view. SentraAI is opinionated by design. We stand for doing fewer things better, and we expect our people to take pride in that standard.
AI Engineer (Conversational AI)
- Location: Abu Dhabi, United Arab Emirates, on site - Employment type: Full time, permanent - Experience: Three years or more building software, with at least one year on LLM based applications that reached real users - Reports to: Chief Technology Officer ## Job Summary As the AI Engineer (Conversational AI) at SentraAI you will design and deliver conversational systems that reach real users, owning the engineering of LLM-based features, retrieval pipelines and conversation flows. You will work onsite with client teams, operate inside existing codebases and cloud accounts, and translate technical tradeoffs to non-technical stakeholders. ## About SentraAI SentraAI is a specialist enterprise AI firm, focused on helping large, regulated organisations move AI and data platforms from experimentation into production safely and sustainably. We work inside enterprise run-states, where governance, operational risk, change control, and long-term ownership are integral to delivery. Our teams are trusted to design and deliver systems, platforms, and operating models that can be run, audited, and evolved, not just launched. We prioritise engineering discipline, architectural clarity, and delivery quality over speed theatre or hype. ## Key Responsibilities ### Design and build conversational systems - Design production conversation flows including error and failure paths - Implement LLM based features and retrieval over enterprise content - Integrate and operate components inside existing codebases and cloud accounts ### Ensure production quality and measurement - Define and measure key performance indicators for conversational features - Diagnose retrieval quality failures and iteratively improve relevance - Run experiments and A/B tests that measure user impact ### Collaborate and explain - Work onsite with client teams to gather requirements and feedback - Explain technical decisions clearly to non-technical stakeholders - Document designs, runbooks and handover materials ### Also in the role - Evidence of measuring an AI system rather than demonstrating it ## Required Qualifications ### Minimum qualifications - Three years or more building software, including at least one year on LLM-based applications that reached real users - Production experience with retrieval over enterprise content and an understanding of why retrieval quality can fail - Strong Python and experience working inside another team’s codebase and cloud account ### Also required - Three years or more building software, with at least one year on LLM based applications that reached real users - Production experience with retrieval over enterprise content, and a clear view on why retrieval quality fails - Strong Python, and comfort working inside someone else's codebase and cloud account - Experience designing conversation flows, including failure paths, not only the ideal path - Able to work onsite with client teams and explain technical decisions to non technical stakeholders ## Advantageous but Not Mandatory - Experience with Databricks or similar enterprise data platforms - Experience with retrieval augmentation pipelines and vector stores - Background in applied evaluation of conversational systems and user metrics ## Why Work for SentraAI Enterprise AI, done properly. We exist to take AI and data out of experimentation and into production environments that are regulated, scrutinised, and expected to work every day. Quality is not optional. SentraAI is built on the belief that engineering discipline, governance by design, and delivery rigour are competitive advantages, not overhead. Clear ownership and accountability. You will be trusted with real responsibility, clear mandates, and meaningful outcomes, not diluted roles or performative activity. Work that survives contact with reality. We design systems, operating models, and decisions that still stand up months and years after go-live, not just at demo time. Run-state matters as much as build-state. We optimise for operability, auditability, and change control from day one, because that is where enterprise value is won or lost. Substance over hype. We deliberately avoid delivery theatre, buzzwords, and novelty for novelty sake. Credibility is earned through execution. Learn from experienced practitioners. You will work alongside people who have built, broken, fixed, and run enterprise systems, and who care deeply about doing the work properly. A firm with a point of view. SentraAI is opinionated by design. We stand for doing fewer things better, and we expect our people to take pride in that standard.
Data Engineer (Databricks)
- Location: Abu Dhabi, United Arab Emirates, on site - Employment type: Full time, permanent - Experience: 5+ years - Reports to: Chief Technology Officer ## Job Summary As the Data Engineer (Databricks) at SentraAI you will design, build and operate Databricks-backed data pipelines and semantic layers to deliver trusted, low-latency data for analytics and agent workloads in Abu Dhabi. You will be measured on pipeline reliability, time-to-insight and the auditability of data access. This is an onsite, full time permanent role for an experienced engineer who can operate Databricks on Azure in production. ## About SentraAI SentraAI is a specialist enterprise AI firm, focused on helping large, regulated organisations move AI and data platforms from experimentation into production safely and sustainably. We work inside enterprise run-states, where governance, operational risk, change control, and long-term ownership are integral to delivery. Our teams are trusted to design and deliver systems, platforms, and operating models that can be run, audited, and evolved, not just launched. We prioritise engineering discipline, architectural clarity, and delivery quality over speed theatre or hype. ## Key Responsibilities ### Databricks and semantic layer - Design, build and tune Databricks Genie spaces including semantic models, synonyms and example queries - Author and validate semantic models and example queries with business users - Structure Unity Catalog access and governance to meet audit requirements ### Pipelines and engineering - Build and maintain PySpark pipelines on Databricks using Delta Lake and medallion architecture - Ingest and transform data on Azure using ADLS and connectors such as Event Hubs or Kafka - Implement automated data quality checks and enforce data contracts ### Performance, operability and handover - Optimise tables and queries for low-latency analytics agent responses - Instrument observability, SLOs and runbooks for production pipelines - Run client training sessions and handover documentation so the platform can be operated without us ## Required Qualifications ### Core capability - Five plus years in data engineering with at least two years working on Databricks - Strong SQL and PySpark skills used in production ETL and transformations - Operational experience with Delta Lake and lakehouse architectures ### Platform and governance - Practical experience operating Databricks on Azure and ADLS in enterprise settings - Experience with Unity Catalog and data access governance under audit - Familiarity with CI CD for data pipelines using Terraform or GitHub Actions ## Advantageous but Not Mandatory - Databricks certification or ability to certify within three months of joining - Experience tuning Databricks for low-latency semantic queries - Previous delivery work inside UAE or GCC regulated buyers - Familiarity with dbt for SQL modelling and orchestration ## Why Work for SentraAI Enterprise AI, done properly. We exist to take AI and data out of experimentation and into production environments that are regulated, scrutinised, and expected to work every day. Quality is not optional. SentraAI is built on the belief that engineering discipline, governance by design, and delivery rigour are competitive advantages, not overhead. Clear ownership and accountability. You will be trusted with real responsibility, clear mandates, and meaningful outcomes, not diluted roles or performative activity. Work that survives contact with reality. We design systems, operating models, and decisions that still stand up months and years after go-live, not just at demo time. Run-state matters as much as build-state. We optimise for operability, auditability, and change control from day one, because that is where enterprise value is won or lost. Substance over hype. We deliberately avoid delivery theatre, buzzwords, and novelty for novelty sake. Credibility is earned through execution. Learn from experienced practitioners. You will work alongside people who have built, broken, fixed, and run enterprise systems, and who care deeply about doing the work properly. A firm with a point of view. SentraAI is opinionated by design. We stand for doing fewer things better, and we expect our people to take pride in that standard.
Data Engineer
- Location: Dubai, United Arab Emirates, on site - Employment type: Full time, permanent - Experience: 5+ years - Reports to: Chief Technology Officer ## Job Summary As the Data Engineer at SentraAI, you will build and operate ETL and data lake pipelines on AWS to deliver reliable data for analytics and AI. You will be measured by reducing data-to-insight lead time to under four hours and maintaining 99.9% pipeline success across Glue and S3 ingestion. This role is not a data scientist or a line manager for engineering teams. ## About SentraAI SentraAI is a specialist enterprise AI firm, focused on helping large, regulated organisations move AI and data platforms from experimentation into production safely and sustainably. We work inside enterprise run-states, where governance, operational risk, change control, and long-term ownership are integral to delivery. Our teams are trusted to design and deliver systems, platforms, and operating models that can be run, audited, and evolved, not just launched. We prioritise engineering discipline, architectural clarity, and delivery quality over speed theatre or hype. ## Key Responsibilities ### AWS data platform delivery - Design and implement AWS Glue ETL jobs and workflows to ingest data from S3 and RDS into the data lake. - Build PySpark and Python ETL pipelines to transform and curate datasets for analytics and model training. - Author Glue schema registry entries and data contracts consumed by Databricks or Redshift tables. - Optimize S3 partitioning, Parquet layout and lifecycle policies to control storage costs in AWS. ### Pipeline orchestration and reliability - Orchestrate pipelines with AWS Step Functions or Airflow, ensuring retries and idempotency for batch jobs. - Implement monitoring and observability using CloudWatch, Prometheus or Grafana for pipeline metrics. - Run incident postmortems and define SLOs to achieve 99.9% pipeline success. ### Data governance and quality - Implement automated data quality checks using Great Expectations and enforce data contracts for upstream owners. - Manage schema evolution and table versioning for Parquet and Delta Lake consumers. - Maintain data lineage and catalogue using AWS Glue Data Catalog or Collibra integrations. ## Required Qualifications ### Core capability - Demonstrate 5+ years building production ETL pipelines on AWS including Glue and S3. - Author Python and PySpark jobs for batch and streaming ETL at scale. - Operate CI CD for data pipelines using Terraform, GitHub Actions or Jenkins. ## Advantageous but Not Mandatory - Experience with Kafka or Kinesis for streaming ingestion. - Familiarity with dbt for transformations and SQL modelling. - Knowledge of Delta Lake or Apache Iceberg table formats. - Experience with cost optimisation and FinOps for AWS data workloads. - Experience automating Glue job deployments with Terraform or CloudFormation. ## Why Work for SentraAI Enterprise AI, done properly. We exist to take AI and data out of experimentation and into production environments that are regulated, scrutinised, and expected to work every day. Quality is not optional. SentraAI is built on the belief that engineering discipline, governance by design, and delivery rigour are competitive advantages, not overhead. Clear ownership and accountability. You will be trusted with real responsibility, clear mandates, and meaningful outcomes, not diluted roles or performative activity. Work that survives contact with reality. We design systems, operating models, and decisions that still stand up months and years after go-live, not just at demo time. Run-state matters as much as build-state. We optimise for operability, auditability, and change control from day one, because that is where enterprise value is won or lost. Substance over hype. We deliberately avoid delivery theatre, buzzwords, and novelty for novelty sake. Credibility is earned through execution. Learn from experienced practitioners. You will work alongside people who have built, broken, fixed, and run enterprise systems, and who care deeply about doing the work properly. A firm with a point of view. SentraAI is opinionated by design. We stand for doing fewer things better, and we expect our people to take pride in that standard.
Data Architect
- Location: Dubai, United Arab Emirates, hybrid - Employment type: Full time, permanent - Reports to: Chief Technology Officer ## Job Summary As the Data Architect at SentraAI, you will design and own our enterprise data platform to enable analytics and AI at scale. You will define cloud data architecture, ETL patterns and data contracts; success measured by reducing data delivery lead time to under four hours and achieving 99.9% pipeline success. This role is not a hands-on data science position or the line manager for engineering teams. ## About SentraAI SentraAI is a specialist enterprise AI firm, focused on helping large, regulated organisations move AI and data platforms from experimentation into production safely and sustainably. We work inside enterprise run-states, where governance, operational risk, change control, and long-term ownership are integral to delivery. Our teams are trusted to design and deliver systems, platforms, and operating models that can be run, audited, and evolved, not just launched. We prioritise engineering discipline, architectural clarity, and delivery quality over speed theatre or hype. ## Key Responsibilities ### Platform architecture and delivery - Design and maintain the enterprise data platform using Databricks and Delta Lake. - Define ETL patterns and orchestrate pipelines with Airflow and dbt for batch workloads. - Own data ingestion from S3 and streaming sources using Kafka or Kinesis. - Set platform capacity, cost controls and security in AWS or Azure cloud accounts. ### Data governance and quality - Establish data contracts, lineage and cataloguing using Collibra or a similar tool. - Implement automated data quality checks with Great Expectations and monitoring dashboards. - Manage schema evolution and table design for Delta Lake consumption. ## Required Qualifications ### Core capabilities - Architect and operate data platforms on AWS or Azure with Databricks. - Build reliable ELT pipelines using dbt, Airflow, Python and SQL at scale. - Design streaming ingestion with Kafka and ensure exactly-once or at-least-once semantics. - Instrument monitoring and observability for pipelines using Prometheus or Grafana. ## Advantageous but Not Mandatory - Experience with MLOps platforms and feature stores. - Worked with dbt at scale in production. - Experience working in regulated financial services or GCC markets. - Hands-on with cost optimisation for cloud data platforms. ## Why Work for SentraAI Enterprise AI, done properly. We exist to take AI and data out of experimentation and into production environments that are regulated, scrutinised, and expected to work every day. Quality is not optional. SentraAI is built on the belief that engineering discipline, governance by design, and delivery rigour are competitive advantages, not overhead. Clear ownership and accountability. You will be trusted with real responsibility, clear mandates, and meaningful outcomes, not diluted roles or performative activity. Work that survives contact with reality. We design systems, operating models, and decisions that still stand up months and years after go-live, not just at demo time. Run-state matters as much as build-state. We optimise for operability, auditability, and change control from day one, because that is where enterprise value is won or lost. Substance over hype. We deliberately avoid delivery theatre, buzzwords, and novelty for novelty sake. Credibility is earned through execution. Learn from experienced practitioners. You will work alongside people who have built, broken, fixed, and run enterprise systems, and who care deeply about doing the work properly. A firm with a point of view. SentraAI is opinionated by design. We stand for doing fewer things better, and we expect our people to take pride in that standard.
AI Revenue Architect
- Location: Abu Dhabi, United Arab Emirates - Employment type: Full time, permanent - Experience: 5 to 10 years - Reports to: Chief Executive Officer ## Job Summary As the AI Revenue Architect at SentraAI, you own new enterprise revenue across the GCC, UK and Germany, and you run the AI sales agents that carry the outbound and qualification work behind it. You sell AI and data platform delivery into regulated buyers in banking, energy, healthcare and government, where procurement is committee driven and a deal is won on credibility, not enthusiasm. Success is measured on qualified pipeline, closed revenue and average deal size in the 2 to 5 million USD band. This is not a people management role and it is not a hands off executive one. There is no human sales team under you. You operate the agents yourself and own what they produce. ## About SentraAI SentraAI is a specialist enterprise AI firm, focused on helping large, regulated organisations move AI and data platforms from experimentation into production safely and sustainably. We work inside enterprise run-states, where governance, operational risk, change control, and long-term ownership are integral to delivery. Our teams are trusted to design and deliver systems, platforms, and operating models that can be run, audited, and evolved, not just launched. We prioritise engineering discipline, architectural clarity, and delivery quality over speed theatre or hype. ## Key Responsibilities ### Running the AI sales agents - Design, deploy and tune the AI sales agents that run outbound into GCC banking and energy accounts - Set the reply and qualified meeting targets each agent carries, and the handover point into your pipeline - Rewrite prompts, targeting and sequencing based on what converts in regulated accounts, not on open rates - Own the quality bar on every agent sent message, because a bad one costs SentraAI the account - Review agent conversations weekly and feed what converts back into targeting and the CRM ### Enterprise commercial ownership - Run the full commercial cycle for 2 to 5 million USD engagements, from qualification to signed SOW - Negotiate scope, payment terms and delivery milestones against real capacity, protecting margin - Navigate committee driven GCC procurement, including tender and RFP processes and vendor registration - Forecast pipeline and closed revenue monthly, with the risk behind each number stated plainly ### Positioning and the AI ecosystem - Build relationships with frontier model providers and the wider enterprise AI ecosystem that open regulated accounts - Turn partner and ecosystem introductions into qualified GCC and UK pipeline, tracked in the CRM - Translate SentraAI delivery capability into propositions a regulated buyer can put to their board - Shape the GCC and UK go to market for agentic AI, and say which segments SentraAI should decline ## Required Qualifications ### Core commercial capability - 5 to 10 years selling technology services or platforms into regulated enterprise buyers - Named, referenceable wins in the 2 to 5 million USD band, not team numbers - Experience carrying committee driven procurement in the GCC or UK, including tender and RFP work - Technical fluency to hold an architecture conversation with a banking or energy CTO, without a presales lead ### AI operating experience - Hands on experience running AI or automated outbound systems, with a concrete example on the CV - Comfort reading conversion data and changing prompts, targeting or sequencing yourself - Judgement about when an AI agent should stop and a human should take the conversation ### Market and relationships - Established relationships across GCC banking, energy, healthcare or government buyers - Working knowledge of how regulated buyers treat data residency and vendor risk in the GCC - Track record building pipeline from a standing start rather than inheriting an account list ## Advantageous but Not Mandatory - Arabic, or a European language useful in the German market - Public sector procurement experience in the GCC - Experience selling into CBUAE, SAMA, QCB or CBK regulated institutions - Background building or operating agentic or autonomous AI systems - Familiarity with CRM and revenue operations tooling ## Why Work for SentraAI Enterprise AI, done properly. We exist to take AI and data out of experimentation and into production environments that are regulated, scrutinised, and expected to work every day. Quality is not optional. SentraAI is built on the belief that engineering discipline, governance by design, and delivery rigour are competitive advantages, not overhead. Clear ownership and accountability. You will be trusted with real responsibility, clear mandates, and meaningful outcomes, not diluted roles or performative activity. Work that survives contact with reality. We design systems, operating models, and decisions that still stand up months and years after go-live, not just at demo time. Run-state matters as much as build-state. We optimise for operability, auditability, and change control from day one, because that is where enterprise value is won or lost. Substance over hype. We deliberately avoid delivery theatre, buzzwords, and novelty for novelty sake. Credibility is earned through execution. Learn from experienced practitioners. You will work alongside people who have built, broken, fixed, and run enterprise systems, and who care deeply about doing the work properly. A firm with a point of view. SentraAI is opinionated by design. We stand for doing fewer things better, and we expect our people to take pride in that standard.
Senior AI & Data Product Owner
- Location: Dubai, United Arab Emirates, hybrid - Employment type: Full time - Reports to: Head of Delivery ## Job Summary The Senior AI & Data Product Owner will own and drive enterprise AI and data products for SentraAI's UAE team, responsible for regulated internal-facing and external-facing products. The role is consultative and operates within agile delivery, applying domain knowledge in at least one regulated sector. ## About SentraAI SentraAI is a specialist enterprise AI firm, focused on helping large, regulated organisations move AI and data platforms from experimentation into production safely and sustainably. We work inside enterprise run-states, where governance, operational risk, change control, and long-term ownership are integral to delivery. Our teams are trusted to design and deliver systems, platforms, and operating models that can be run, audited, and evolved, not just launched. We prioritise engineering discipline, architectural clarity, and delivery quality over speed theatre or hype. ## Key Responsibilities ### Product ownership - Own and drive enterprise AI and data product development for regulated, internal-facing and external-facing products. ### Delivery and process - Operate within agile delivery, working consultatively in product development. ### Consulting and stakeholder engagement - Act as a consultant and engage consultatively with stakeholders. ### Sector engagement - Apply domain knowledge in at least one of finance, banking, energy and utilities, oil and gas, or healthcare. ### Technology and models - Maintain awareness of frontier models. ## Required Qualifications ### Core product capability - Deep experience in enterprise product development. ### Experience - Roughly 10 years' experience. ### Delivery approach - Comfortable working in agile, consultative ways. ### Consultative practice - Experience working as a consultant. ### Sector knowledge - Knowledge of at least one of the following sectors: finance, banking, energy and utilities, oil and gas, or healthcare. ### Technology familiarity - Awareness of frontier models. ## Why Work for SentraAI - Enterprise AI, done properly. We exist to take AI and data out of experimentation and into production environments that are regulated, scrutinised, and expected to work every day. - Quality is not optional. SentraAI is built on the belief that engineering discipline, governance by design, and delivery rigour are competitive advantages, not overhead. - Clear ownership and accountability. You will be trusted with real responsibility, clear mandates, and meaningful outcomes, not diluted roles or performative activity. - Work that survives contact with reality. We design systems, operating models, and decisions that still stand up months and years after go-live, not just at demo time. - Run-state matters as much as build-state. We optimise for operability, auditability, and change control from day one, because that is where enterprise value is won or lost. - Substance over hype. We deliberately avoid delivery theatre, buzzwords, and novelty for novelty's sake. Credibility is earned through execution. - Learn from experienced practitioners. You will work alongside people who have built, broken, fixed, and run enterprise AI systems. - A firm with a point of view. SentraAI is opinionated by design. We stand for doing fewer things better, and we expect our people to take pride in that standard.
Platform Engineer
- Location: Dubai, United Arab Emirates, on site - Employment type: Full time - Reports to: Chief Technology Officer ## Job Summary You will own the AWS platform our AI workloads run on, building and running EKS clusters, writing the Terraform for accounts and networking, and owning the CI/CD pipelines the delivery teams ship through. You will also run the Kafka estate, managing topics, schemas and consumer lag, and keep the platform healthy under production load. ## About SentraAI SentraAI is a specialist enterprise AI firm, focused on helping large, regulated organisations move AI and data platforms from experimentation into production safely and sustainably. We work inside enterprise run-states, where governance, operational risk, change control, and long-term ownership are integral to delivery. Our teams are trusted to design and deliver systems, platforms, and operating models that can be run, audited, and evolved, not just launched. We prioritise engineering discipline, architectural clarity, and delivery quality over speed theatre or hype. ## Key Responsibilities ### Platform ownership - Own the AWS platform our AI workloads run on. ### Kubernetes and container platform - Build and run EKS clusters. - Operate Kubernetes in production properly, not just deploy to it. ### Infrastructure as code - Write the Terraform for the accounts and networking. ### CI/CD - Own the CI/CD pipelines the delivery teams ship through. ### Kafka operations - Run our Kafka estate, including topics, schemas, and consumer lag, and keep it healthy under production load. ### Reliability and governance - Be on the hook for uptime and change control in a regulated environment. ## Required Qualifications ### Core capability - Strong Terraform and AWS. ### Production operations - Demonstrable experience running Kubernetes in production, not just deploying to it, specifically EKS clusters. ### Platform and pipeline ownership - Experience owning CI/CD pipelines the delivery teams ship through. ### Streaming platform skills - Experience running Kafka in production, including operating the estate, topics, schemas, and monitoring consumer lag. ### Regulated environment - Comfortable being on the hook for uptime and change control in a regulated environment. ## Advantageous but Not Mandatory - Service mesh. - Observability tooling. - Kafka Connect. ## Why Work for SentraAI - Enterprise AI, done properly. We exist to take AI and data out of experimentation and into production environments that are regulated, scrutinised, and expected to work every day. - Quality is not optional. SentraAI is built on the belief that engineering discipline, governance by design, and delivery rigour are competitive advantages, not overhead. - Clear ownership and accountability. You will be trusted with real responsibility, clear mandates, and meaningful outcomes, not diluted roles or performative activity. - Work that survives contact with reality. We design systems, operating models, and decisions that still stand up months and years after go-live, not just at demo time. - Run-state matters as much as build-state. We optimise for operability, auditability, and change control from day one, because that is where enterprise value is won or lost. - Substance over hype. We deliberately avoid delivery theatre, buzzwords, and novelty for novelty's sake. Credibility is earned through execution. - Learn from experienced practitioners. You will work alongside people who have built, broken, fixed, and run enterprise AI systems. - A firm with a point of view. SentraAI is opinionated by design. We stand for doing fewer things better, and we expect our people to take pride in that standard.
MLOps Engineer
- Location: Dubai, United Arab Emirates - Employment type: Full time - Reports to: Chief Technology Officer Job Summary As an LLM / MLOps Engineer at SentraAI, you are responsible for operationalising, deploying, and governing machine learning and LLM-based systems in production. This role exists to ensure AI systems are reliable, observable, reproducible, and controllable once live. You will own pipelines, deployment patterns, monitoring, and controls that allow AI systems to operate safely within enterprise run-states. This is a systems and platform-focused role, not a research position. About SentraAI SentraAI is a specialist enterprise AI firm, focused on helping large, regulated organisations move AI and data platforms from experimentation into production safely and sustainably. We work inside enterprise run-states, where governance, operational risk, change control, and long-term ownership are integral to delivery. Our teams are trusted to design and deliver systems, platforms, and operating models that can be run, audited, and evolved, not just launched. We prioritise engineering discipline, architectural clarity, and delivery quality over speed theatre or hype. Key Responsibilities LLM and ML Operations • Build and operate end-to-end ML and LLM pipelines from training through inference • Manage model registries, versioning, and promotion workflows • Package and deploy models using containerised and cloud-native patterns Deployment, Reliability, and Scale • Design and operate inference services for real-time and batch workloads • Implement rollout, rollback, and blue/green deployment strategies • Ensure systems meet performance, availability, and cost expectations Observability and Governance • Implement monitoring for model performance, drift, and anomalous behaviour • Instrument AI systems for logging, metrics, and traceability • Embed validation, guardrails, and runtime controls for LLM-based systems • Support audit, risk, and compliance requirements Platform and Collaboration • Work closely with AI/ML Engineers to productionise models • Partner with data engineering, security, and platform teams • Contribute to platform standards, runbooks, and reference architectures Required Qualifications Core Engineering Capability • Strong proficiency in Python for production systems • Experience with CI/CD and automation for ML systems • Strong understanding of distributed systems fundamentals MLOps and LLM Ops Tooling • MLflow or Weights and Biases • Docker and containerised deployments • FastAPI or equivalent inference frameworks • Kubernetes or managed equivalents LLM Operations • Experience deploying and operating LLM-based applications • Familiarity with vector databases such as Pinecone, Weaviate, or FAISS • Understanding of prompt orchestration and runtime controls Cloud Platforms • Strong experience with AWS, Azure, or GCP Advantageous but Not Mandatory • Experience operating AI systems in regulated enterprise environments • Exposure to AI security, guardrails, or red-teaming practices • Experience with cost optimisation or FinOps for AI workloads • Familiarity with SOC, monitoring, or incident response processes Why Work for SentraAI • Enterprise AI, done properly. We exist to take AI and data out of experimentation and into production environments that are regulated, scrutinised, and expected to work every day. • Quality is not optional. SentraAI is built on the belief that engineering discipline, governance by design, and delivery rigour are competitive advantages, not overhead. • Clear ownership and accountability. You will be trusted with real responsibility, clear mandates, and meaningful outcomes, not diluted roles or performative activity. • Work that survives contact with reality. We design systems, operating models, and decisions that still stand up months and years after go-live, not just at demo time. • Run-state matters as much as build-state. We optimise for operability, auditability, and change control from day one, because that is where enterprise value is won or lost. • Substance over hype. We deliberately avoid delivery theatre, buzzwords, and novelty for novelty’s sake. Credibility is earned through execution. • Learn from experienced practitioners. You will work alongside people who have built, broken, fixed, and run enterprise AI systems. A firm with a point of view. SentraAI is opinionated by design. We stand for doing fewer things better, and we expect our people to take pride in that standard
9 open positions