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
