AI Engineer

KEY RESPONSIBILITIES

• Design and build agentic AI solutions from concept to pilot or production, including agent role definition, autonomy boundaries, tool/data scopes, guardrails, and evaluation criteria.
• Implement agent loops, tool-use patterns, context engineering, retrieval/RAG flows, HITL approval journeys, tracing, telemetry, and audit capture.
• Select and justify models based on latency, cost, residency, reliability, and use-case fit; tune solutions for performance and operational cost.
• Develop reusable Agent JD templates, prompt/context patterns, orchestration patterns, and evaluation assets that can be adopted across teams.
• Partner with governance, platform, and integration teams to make agents gate-ready by design, including prompt-injection, PII leakage, and reliability controls.
• Support complex and multi-agent solutions, including orchestration, memory, retrieval, reasoning, and agent-to-agent composition.
• Move solutions through sandbox, staging, and production promotion paths, ensuring each agent is observable, versioned, tested, and auditable.
• Mentor junior engineers and contribute to a strong engineering culture around quality, speed, learning, and responsible AI delivery.

KEY REQUIREMENTS

• Strong software engineering background in Python and/or C#, with experience building production-grade APIs, services, or cloud-native applications.
• Hands-on experience with LLMs, agent frameworks, and agentic design patterns such as Semantic Kernel, Microsoft Agent Framework / AutoGen, LangGraph, or comparable frameworks.
• Practical experience with RAG, vector search, prompt/context engineering, system prompt design, tool calling, and model evaluation.
• Ability to build and maintain evaluation sets, regression tests, and acceptance criteria for agent behaviour, reliability, and safety.
• Experience integrating APIs, data sources, and tools into AI workflows; comfortable debugging across application, data, and model layers.
• Understanding of cloud-native delivery, observability, CI/CD, secrets management, telemetry, and secure software development practices.
• Strong communication skills with the ability to explain technical trade-offs to product, business, governance, and leadership stakeholders.

PREFERRED QUALIFICATIONS

• Azure AI Foundry, Azure OpenAI, Azure AI Search, Functions, Container Apps, Cosmos DB, Redis, OpenTelemetry, or equivalent cloud AI stack experience.
• Experience with bilingual or Arabic/English AI products, evaluation design, and user-facing AI experiences.
• Experience with multi-modal AI, including vision, voice, document intelligence, or video/avatar experimentation.
• Prior work in government, regulated, sovereign cloud, or enterprise environments where auditability and data residency matter.
• Technical leadership or player-coach experience, including mentoring engineers and raising engineering standards.

TECH STACK / TOOLS

Azure AI Foundry - Semantic Kernel - LangGraph - Azure OpenAI - AI Search - Cosmos DB - Redis - Functions, Container Apps - Eval harness - OpenTelemetry

FIRST 90 DAYS SUCCESS

• At least one agent progresses through the full factory path into production or production-equivalent validation on a real source, with a passing evaluation bundle.
• A reusable Agent JD, prompt/context, or orchestration pattern is contributed to the team library.
• The AI engineering team improves first-time gate readiness through better patterns, testing, and documentation.

This role is not. A pure model research role or a platform/landing-zone owner. This role builds working agents and the patterns that make them reliable.