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




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

Valuable 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 (India)
🏢 CodeForce 360
📍 India