Job Description
Role & responsibilities
Role Purpose
Own and deliver endtoend GenAI and agentic AI modules, driving design decisions, best practices, and mentoring JL4 engineers.
Key Responsibilities
- Design and implement productiongrade GenAI architectures
- Own AWS Bedrock integrations (models, KBs, guardrails, cost controls)
- Build agentic systems with planning, memory, retries, and state
- Lead LangGraph workflows (conditional routing, interrupts, HITL)
- Define evaluation, observability, and cost optimisation strategies
- Drive CI/CD, Docker, IaC, and security practices
- Mentor juniors and participate in design reviews
MustHave Skills
Advanced Python - Async patterns, multiprocessing, Profiling, performance tuning, Clean project structuring & testing strategy
AWS Bedrock - Model selection & access policies, Streaming, tool-use, guardrails, Knowledge base design & scaling,
GenAI / Agentic AI - Task decomposition, long-running workflows, Multi-agent patterns, Evaluation, grounding, hallucination control, Cost, latency, success KPIs. LangChain & LangGraph nodes, edges, interrupts, LCEL, agents, evaluators, Persistence, resumes, HITL
DevOps & Platform Docker multi-stage builds,CI/CD ownership, Terraform, secrets , management, SAST/DAST awareness
Good to Have
Production RAG optimization experience, Responsible AI / Guardrails exposure, Drift detection & monitoring, Strong articulation & stakeholder interaction, Ownership mindset, Mentoring & technical leadership
Preferred candidate profile