Senior Artificial Intelligence Engineer

COMPANY OVERVIEW ARRAY, a software development company headquartered in Bahrain, is growing its Quant Dev team. We’re looking for a Senior AI Engineer with strong mathematical, machine learning and software engineering foundations to join us in Bahrain. Backed by a sovereign wealth fund, we offer long-term job stability and the chance to grow with us. THE TEAM Quant Dev combines mathematical rigour and engineering excellence. The team builds great products at enterprise scale, using AI to turn multi-modal data into impactful decisions. We come largely from banks, asset managers and applied science backgrounds, and we work where research meets production: applied, deployed and in the hands of clients. THE ROLE We’re looking for a senior engineer who can take an AI product from requirement to production and lead the build. You combine strong mathematical and machine learning foundations – in classical ML, in LLM and retrieval systems, or both – with software engineering of a high standard. You’ll work with the commercial team to understand what is needed, design the solution and estimate the work, then assemble and lead a small team of Quant Dev engineers to deliver it. This is an applied role: informed by research, but measured by what reaches production and what clients use. KEY RESPONSIBILITIES • Applied AI/ML: Own the model and system choices inside deployed products – classical ML or LLM, retrieval and agent systems – covering selection, training or prompting, evaluation, deployment, monitoring and improvement. • Product Engineering: Design, build, deploy and operate production-grade software at enterprise scale, owning features end to end, on cloud or on-prem. • Technical Leadership: Assemble and lead junior engineers on a build – plan the work, set the design, review the code, unblock and mentor. • Engineering Standards: Raise the bar through code review, testing, sound design and expert use of AI coding agents – help the team build faster and safer. • Solution Design: Work with the commercial team to understand requirements, design the solution and estimate effort and risk – producing scopes that win deals and hold in delivery. • Product Conception: Contribute to the ideation and shaping of AI-powered products. Minimum of 5 years of hands-on experience building and deploying software products, including several years delivering AI/ML systems to production – not prototypes or research notebooks. • Depth in at least one of: classical machine learning (model selection, training, evaluation and the mathematics behind them) or LLM systems (retrieval, RAG, agents, evaluation and fine-tuning). • Strong mathematical and statistical foundations (probability, statistics, linear algebra, optimisation) – able to reason about model behaviour, not just invoke libraries. • Software engineering excellence in Python: system design, testing, version control, code review and CI/CD – beyond modelling code. • Experience leading other engineers on a delivery: planning, design ownership, code review and mentoring. • Able to engage with the commercial team: understand requirements, design solutions and estimate effort. • Independent problem-solver and genuine team player, with excellent verbal and written communication skills. • Academic background: Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Artificial Intelligence or a related quantitative field, or a Bachelor’s with an equivalent record of applied mathematical and ML depth. NICE-TO-HAVE SKILLS • Experience delivering AI products into regulated or operationally critical domains – such as financial services, insurance, government or heavy industry – and a record of picking up new domains quickly. • Familiarity with MLOps and LLM evaluation tooling: experiment tracking, model and prompt evaluation, monitoring. • Experience with multi-modal data – time series, documents, video – in production products. • Containerisation and orchestration (e.g., Docker, Kubernetes). • Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying AI applications; on-prem deployment experience is equally welcome. • Experience with startup culture – adaptability to a fast-paced, ever-changing environment.

Minimum of 5 years of hands-on experience building and deploying software products, including several years delivering AI/ML systems to production – not prototypes or research notebooks. Depth in at least one of: classical machine learning (model selection, training, evaluation and the mathematics behind them) or LLM systems (retrieval, RAG, agents, evaluation and fine-tuning). Strong mathematical and statistical foundations (probability, statistics, linear algebra, optimisation). Software engineering excellence in Python: system design, testing, version control, code review and CI/CD – beyond modelling code. Experience leading other engineers on a delivery: planning, design ownership, code review and mentoring. Able to engage with the commercial team: understand requirements, design solutions and estimate effort. Academic background: Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Artificial Intelligence or a related quantitative field, or a Bachelor’s with an equivalent record of applied mathematical and ML depth.

Applied AI/ML: Own the model and system choices inside deployed products – classical ML or LLM, retrieval and agent systems – covering selection, training or prompting, evaluation, deployment, monitoring and improvement. Product Engineering: Design, build, deploy and operate production-grade software at enterprise scale, owning features end to end, on cloud or on-prem. Technical Leadership: Assemble and lead junior engineers on a build – plan the work, set the design, review the code, unblock and mentor. Engineering Standards: Raise the bar through code review, testing, sound design and expert use of AI coding agents – help the team build faster and safer. Solution Design: Work with the commercial team to understand requirements, design the solution and estimate effort and risk – producing scopes that win deals and hold in delivery. Product Conception: Contribute to the ideation and shaping of AI-powered products.