Hands-on experience building agentic AI applications using LangChain, LangGraph, or equivalent orchestration frameworks.

- Solid Python proficiency with LLM APIs (Anthropic/OpenAI), RAG architectures, vector databases, and embeddings

- Experience deploying AI solutions on AWS/Azure/GCP with Docker/Kubernetes, CI/CD, and LLMOps/MLOps practices

- Ability to implement agentic capabilities task planning, tool use, retrieval, reasoning, and memory modules

- Experience developing evaluation frameworks for hallucination mitigation, accuracy, and reasoning quality

- Working knowledge of regulated-industry practices GxP, 21 CFR Part 11, HIPAA, auditability, and traceability

- Proven ability to lead technical work independently and mentor junior/mid-level engineers





- Strong communication skills; comfortable engaging with US-based stakeholders across time zones.

Good to Have

- Familiarity with Model Context Protocol (MCP), tool/function calling, and AI gateways

- Experience with observability and monitoring dashboards for agent performance and drift detection

- Prior exposure to clinical development, pharmacovigilance, or regulatory domain workflows

- Experience with life sciences, pharma, or healthcare IT environments

Contribution to reusable frameworks, shared components, or architecture standards at portfolio level.

📌 Artificial Intelligence Engineer (Bengaluru)
🏢 CodeForce 360
📍 Bengaluru