About this role
Key Accountabilities
• Design and delivery of AI‑enabled application components and agent workflows • Reliability, performance, and operational supportability of deployed solutions • Adherence to enterprise engineering standards, security controls, and data governance requirements Principal Responsibilities
• Design, build, and test multi‑step agent workflows using established patterns such as ReAct, planner‑executor, and tool‑chaining • Integrate LLMs (i.e. Claude and OpenAI) with enterprise APIs and internal systems, including robust handling of retries, edge cases, and degraded states • Implement tool calling, function orchestration, and compensating actions to ensure workflows remain stable under failure conditions • Design and implement human‑in‑the‑loop controls, including approvals, escalations, and exception handling where required by business logic or risk considerations • Collaborate with product managers, domain experts, and technical stakeholders to refine requirements and translate them into technical designs • Develop, maintain, and version prompt logic and supporting documentation in line with agreed standards • Build and manage agent memory and retrieval mechanisms using vector databases and retrieval‑augmented generation (RAG), ensuring context remains relevant and high‑signal • Deploy AI services to production environments and actively monitor logs, traces, and metrics to detect and resolve issues • Contribute to test coverage, operational runbooks, and incident response practices in collaboration with QA and operations teams • Support continuous improvement of system reliability, performance, and maintainability
Knowledge, Skills & Experience Essential
• Minimum 4 years’ experience developing backend or service-based systems using C# and/or Python
• At least 1 year of hands‑on experience working with large language models, prompt engineering, or AI‑enabled systems • Strong analytical and debugging skills with the ability to reason across APIs, data flows, and AI system behavior • Ability to clearly communicate technical decisions and trade‑offs to technical and non‑technical stakeholders • Demonstrated ability to learn and adapt in a rapidly evolving technology environment Technical Skills (Required)
• Programming: C#, Python (production services, async workflows, automated testing) • Cloud Platform: Azure (compute, storage, identity, deployment pipelines) • LLM Integration: Claude and/or OpenAI APIs (prompting, tool calling, rate limits, error handling) • Agent Orchestration: Azure AI Foundry, Microsoft Agent Framework; optional alternatives include LangGraph and LangChain. • Vector Databases: Pinecone or equivalent (indexing, retrieval, relevance tuning) • APIs & Integration: RESTful APIs, enterprise authentication, service‑to‑service integration • Observability: Application logging, metrics, and tracing in production environments Desirable
• Docker and Azure Container Services • SQL Server or other relational databases • Azure Cosmos DB • Experience in regulated or compliance driven environments • AI Governance and AI Security is a plus WTW is an Equal Opportunity Employer