Proven experience in building production-grade agentic AI systems for real users.
Strong command of state management, concurrency, and authorization in multi-user systems.
Substantial experience in software development with Python, TypeScript/JavaScript, C#, or Java.
Hands-on integration experience with enterprise APIs and data platforms.
Familiarity with modern AI application patterns, including retrieval-augmented generation and agent orchestration.
Strong practical knowledge of Azure cloud services and application management.
Demonstrated ability to rapidly prototype using AI-assisted development.
Responsibilities
Design and build agentic AI applications using Microsoft Fabric and Azure AIs.
Lead a multi-functional team in problem-solving, prototyping, and production.
Run an iterative build cycle to refine and finalize solutions swiftly.
Ensure the quality of shipped products focusing on security and reliability.
Select appropriate technology approaches, using low-code or custom code as needed.
Prepare data for AI readiness with proper modeling and governance.
Document reusable technical patterns and components for the team.
Adapt quickly to new business domains and challenge requirements constructively.
Benefits
Opportunity to work at the intersection of AI technology and enterprise systems.
Exposure to cutting-edge tools and platforms like Microsoft Fabric and Azure AI.
Collaboration within a dynamic, multi-functional team environment.
Focus on rapid development cycles, enhancing skills in agile methodologies.
Opportunity to lead projects with substantial autonomy and influence.
Full Job Description
Job Description What You Will Do
Design, build and harden agentic AI applicationsthat read from and write to enterprise systems of record, grounded onMicrosoft Fabric and Azure AI services.
Embed with a Corporate Function team as the technicallead of a small, multi-functional pod - moving from problem, to prototype,to production at pace.
Run a tight, iterative build cycle: align on theoutcome, prototype, gather feedback, refine and finalise, typically withinone to two weeks per loop.
Own the quality of what you ship end to end - security,reliability, scalability, observability, and safe, governed write-back tosource systems.
Make the right build call for the problem: low-code andagent-builder platforms where they fit, custom code where they do not.
Ensure the data behind each solution is AI-ready -modelled, governed and documented in Fabric, with lineage and accesscontrol that will stand up to audit.
Set and document the reusable technical patterns,components and guardrails the team applies across every engagement.
Become credible in a new business domain quickly, andchallenge requirements constructively to land on the right solution ratherthan the requested one.
Requirements
Required Qualifications
Proven experience building agentic or multi-agent AIsystems that run in production and serve real users - working systems, notdemonstrations.
Strong command of state management, concurrency,idempotency and authorisation for systems that act on a system of recordon behalf of many users.
Substantial software development experience in at leastone language such as Python, TypeScript/JavaScript, C# or Java -you can architect, write, review and debug production code.
Hands-on integration experience with enterprise APIsand data platforms, including designing safe read and write paths andhandling failure gracefully.
Working knowledge of modern AI application patterns -retrieval-augmented generation, prompt and context design, agentorchestration, tool use and protocols such as MCP.
Strong, hands-on command of a major cloud platform,ideally Azure - able to independently provision, configure, deploy, secureand operate cloud resources, owning an application end to end rather thanonly consuming pre-built services.
Demonstrated ability to prototype rapidly, usingAI-assisted development and fast iteration to turn a loosely defined ideainto something usable in days.
The judgement and autonomy of a senior individualcontributor - able to make sound architecture and feasibility calls alone,under time pressure, and explain them to non-technical stakeholders.
