WTW
Description 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 Qualifications 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
WTW
