Agentic AI Developer Night Shift

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
  
  

• 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
  
  

• 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
  
  

• 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
  
  

• 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