Artificial intelligence Developer (Pro Code)

Willis Towers Watson is a leading global advisory broking and solutions company that helps clients around the world turn risk into a path for growth. With roots dating to 1828 Willis Towers Watson has 45000 employees serving more than 140 countries. We design and deliver solutions that manage risk optimize benefits cultivate talent and expand the power of capital to protect and strengthen institutions and individuals. Our unique perspective allows us to see the critical intersections between talent assets and ideas the dynamic formula that drives business performance. Together we unlock potential. Learn more at .

Role Summary

We are looking for a pro-code AI (Artificial intelligence) Developer who builds production-grade AI (Artificial intelligence) systems in code. You will design and build AI (Artificial intelligence) agents RAG (Retrieval-Augmented Generation) pipelines and AI-powered (Artificial intelligence) applications primarily in Python orchestrating LLMs (Large Language Models.)with frameworks such as LangChain LangGraph and AutoGen integrating them into enterprise systems via APIs(Application Programming Interface) and MCP(Model Context Protocol) and deploying them on the cloud (including Azure AI (Artificial intelligence) Foundry). The ideal candidate has a strong software-engineering foundation a strong bias to build and can move from a loosely defined idea to a working proof-of-concept in days not weeks.

What Youll Do

• Design and build AI (Artificial intelligence) agents RAG (Retrieval-Augmented Generation) pipelines and AI-powered (Artificial intelligence) applications in code (primarily Python) orchestrating LLMs(Large Language Models.) with frameworks such as LangChain LangGraph and AutoGen.

• Implement advanced RAG (Retrieval-Augmented Generation) techniques hybrid search re-ranking contextual chunking and long-context strategies and agentic orchestration patterns (ReAct plan-and-execute multi-agent).

• Build and integrate APIs(Application Programming Interface) and enterprise connectors including MCP-based integrations to connect AI (Artificial intelligence) capabilities with enterprise systems and data sources.

• Deploy configure and operate AI (Artificial intelligence) workloads on the cloud owning solutions end-to-end from prototype to production.

• Design AI (Artificial intelligence) solutions that scale accounting for performance throughput latency cost and reliability as usage grows from POC (Proof of Concept) to enterprise scale.

• Rapidly prototype: take a loosely defined idea or business problem and produce a working proof-of-concept quickly then iterate based on feedback.

• Apply sound engineering judgment error handling evaluation observability security and access considerations across the solutions you build.

Required Qualifications

• Strong hands-on software development experience in Python with a solid engineering foundation (you can design write test and debug production code).

• Hands-on experience with LangChain LangGraph and/or AutoGen and with agentic orchestration patterns for building multi-agent or agentic AI (Artificial intelligence) systems.

• Proven experience building RAG (Retrieval-Augmented Generation) systems including advanced techniques such as hybrid search re-ranking contextual chunking and long-context strategies.

• Experience designing and consuming APIs(Application Programming Interface) and integrations; familiarity with MCP (Model Context Protocol) as an emerging integration pattern.

• Strong hands-on command of cloud concepts on at least one major provider (Azure preferred; AWS or GCP considered) able to independently provision configure develop against deploy and operate AI (Artificial intelligence) workloads and cloud resources. Hands-on experience with Azure AI (Artificial intelligence) Foundry (or an equivalent managed AI (Artificial intelligence) platform).

• Understanding of how to design and scale AI (Artificial intelligence) solutions for production performance throughput latency cost optimization and reliability including patterns such as caching asynchronous processing load handling and horizontal scaling.

• Demonstrated ability to rapidly prototype translating an idea into a functional proof-of-concept quickly using AI-assisted (Artificial intelligence) development and fast iteration.

Preferred Qualifications

• Experience with AI (Artificial intelligence) evaluation and observability tooling (e.g. ragas LangSmith Promptflow evals Azure Monitor).

• Familiarity with AI (Artificial intelligence) safety responsible AI principles and enterprise guardrail patterns (content filtering grounding checks).

• Working knowledge of low-code AI (Artificial intelligence) platforms (Microsoft Copilot Studio Power Platform) or agent-builder platforms (Lyzr Moveworks) for rapid delivery where they are the right fit.

• Experience integrating with Microsoft 365 and Dataverse or an equivalent enterprise ecosystem.

What Makes You a Fit

You are first and foremost a strong engineer who has moved into AI (Artificial intelligence) comfortable living in code reasoning about architecture and owning a solution from prototype to production. You reach for low-code tools when they are genuinely the fastest path but your default is to build in code and you would rather ship a rough proof-of-concept today than a perfect specification next month.

The Application Process:

• Stage 1: Online application and recruiter review
• Stage 2: Pre-recorded video interview
• Stage 3: Live video or in person interview with hiring manager and team
• Stage 4: Offer and onboarding

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• Bachelor or Masters degree in Computer Science Information Technology Business Administration or a related field.

Were committed to equal employment opportunity and provide application interview and workplace adjustments and accommodations to all applicants. If you foresee any barriers from the application process through to joining WTW please email.