Discovered MENA
API Engineer
Abu Dhabi, UAEPosted yesterday
- Salary
- AED 12k–18k a month· est.
- Job type
- Contract
- Level
- Senior
- Field
- AI & Machine Learning
- Work mode
- On site
About the role
API Engineer (AI & Agent Platforms) Location: Abu Dhabi, UAE Contract: 12 months, extendable Sector: Financial Services / Banking Client: Leading financial services organisation in Abu Dhabi About the Role Our client, a leading financial services organisation in Abu Dhabi, is building production-grade AI and agent capabilities that sit at the core of how the business operates. They are looking for an API Engineer to design, build and scale the APIs and platform services that power these capabilities across the organisation. This is not a role for someone who has built a handful of isolated proofs of concept. The successful candidate will have lived through the full lifecycle of AI agents in a regulated environment, understands where they break, and can engineer reusable, scalable platforms that multiple teams and products can build on. They will operate with a high degree of autonomy, take ownership of problems end to end, and help set the technical direction. Key Responsibilities • Design, build and maintain secure, scalable APIs and platform services that expose LLM, agent and ML capabilities to internal teams and business applications • Architect agent-based systems across their full lifecycle: design, orchestration, tool integration, evaluation, deployment, monitoring and continuous improvement • Identify and resolve core agent failure modes, including reliability, hallucination, latency, cost, tool-calling errors and context management, and embed those lessons into the platform • Build multi-dimensional, reusable capabilities and shared infrastructure rather than one-off solutions • Design and run real-world A/B tests and controlled rollouts of AI features at scale, using results to drive technical decisions • Work with product, data science, risk, security and compliance stakeholders to ensure solutions meet the standards expected in banking • Own delivery end to end, from ambiguous problem statement through to production, making independent decisions and managing trade-offs • Anchor technical direction, set engineering standards and mentor other engineers • Contribute to team growth and, where appropriate, step into tech lead responsibilities, guiding delivery across a team Essential Experience Domain background • Proven background in financial services or banking, with a strong understanding of the security, governance and regulatory context in which AI systems must operate AI and agent architecture depth • Extensive, hands-on experience across the entire lifecycle of AI agents in production, not surface-level familiarity • Demonstrable understanding of where agents fail and the practical techniques used to make them robust • Strong working knowledge of LLMs and core machine learning foundations Platform engineering at scale • Track record of building production-grade, scalable platforms and capabilities, as opposed to isolated or experimental projects • Strong API design and engineering skills (RESTful and event-driven patterns, authentication and authorisation, versioning, observability and performance) • Experience deploying and experimenting with AI systems at scale, including live A/B testing Ownership and autonomy • Ability to work beyond rigid task definitions, handle ambiguity and make sound decisions independently • Evidence of anchoring technical direction on previous teams or programmes Leadership potential • Proven ability, or a clear trajectory, to expand into a tech lead or management role, guiding teams and owning end-to-end delivery Desirable • Experience with cloud-native and containerised environments • Familiarity with agent orchestration frameworks, retrieval and evaluation tooling • Experience working with UAE or wider GCC regulatory and data-residency requirements • Prior experience leading or mentoring engineers
Requirements
- Essential Experience
- Domain background
- • Proven background in financial services or banking, with a strong understanding of the security, governance and regulatory context in which AI systems must operate
- AI and agent architecture depth
- • Extensive, hands-on experience across the entire lifecycle of AI agents in production, not surface-level familiarity
- • Demonstrable understanding of where agents fail and the practical techniques used to make them robust
- • Strong working knowledge of LLMs and core machine learning foundations
- Platform engineering at scale
- • Track record of building production-grade, scalable platforms and capabilities, as opposed to isolated or experimental projects
- • Strong API design and engineering skills (RESTful and event-driven patterns, authentication and authorisation, versioning, observability and performance)
- • Experience deploying and experimenting with AI systems at scale, including live A/B testing
- Ownership and autonomy
- • Ability to work beyond rigid task definitions, handle ambiguity and make sound decisions independently
- • Evidence of anchoring technical direction on previous teams or programmes
- Leadership potential
- • Proven ability, or a clear trajectory, to expand into a tech lead or management role, guiding teams and owning end-to-end delivery
Responsibilities
- Design, build and maintain secure, scalable APIs and platform services that expose LLM, agent and ML capabilities to internal teams and business applications
- Architect agent-based systems across their full lifecycle: design, orchestration, tool integration, evaluation, deployment, monitoring and continuous improvement
- Identify and resolve core agent failure modes, including reliability, hallucination, latency, cost, tool-calling errors and context management, and embed those lessons into the platform
- Build multi-dimensional, reusable capabilities and shared infrastructure rather than one-off solutions
- Design and run real-world A/B tests and controlled rollouts of AI features at scale, using results to drive technical decisions
- Work with product, data science, risk, security and compliance stakeholders to ensure solutions meet the standards expected in banking
- Own delivery end to end, from ambiguous problem statement through to production, making independent decisions and managing trade-offs
- Anchor technical direction, set engineering standards and mentor other engineers
- Contribute to team growth and, where appropriate, step into tech lead responsibilities, guiding delivery across a team
Skills
- APIs (RESTful)
- OAuth / authentication and authorization
- API versioning
- Observability
- Performance tuning
- LLMs
- Machine learning foundations
- Agent architectures
- AI systems at scale
- A/B testing
- Platform engineering
- Cloud-native environments
- Containerised environments
- Agent orchestration frameworks
- Tool integration
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