Product Engineering Lead / Architect Agentic AI Platform!

MaxisAI | Full-Time | India

MaxisAI is building an agentic AI platform for clinical and life sciences. We're looking for a hands-on Engineering Lead who will own the full engineering lifecycle, from architecture and coding to CI/CD, quality, and compliance.

This is a player-coach role: about 60% hands-on architecture and coding, 40% team leadership. You'll write agent code yourself, debug agents in production from their traces, and turn prototypes into production-grade, GxP-compliant services.

What you'll do

- Architect and build multi-agent systems on AWS Bedrock (Agents, AgentCore, Knowledge Bases, Guardrails) using LangChain, LangGraph, and LangSmith
- Build RAG pipelines, tool/function calling, agent memory, and human-in-the-loop workflows
- Design microservices with domain-driven design, API gateways, and event-driven patterns (SQS, SNS, EventBridge, Kafka)
- Deploy on AWS (EKS/ECS, Lambda, Step Functions) with Terraform or CDK
- Run model selection and evals across Claude, Llama, and Titan; optimise cost and latency
- Establish LLMOps: prompt versioning, eval frameworks, hallucination controls, and eval-gated deployments
- Drive an AI-native development lifecycle using Claude Code,



Cursor, and GitHub Copilot
- Ensure AI outputs are traceable, auditable, and explainable for GxP use, including validation artefacts (IQ/OQ/PQ, traceability matrices)
- Lead, mentor, and grow a team of frontend, backend, and platform engineers
- Own the technical roadmap, capacity planning, and delivery commitments with Product

What we're looking for

- 910 years in software engineering, including 4+ years in an engineering lead role
- 23 years of hands-on agentic AI experience (mandatory)
- Has personally architected and shipped production agentic or multi-agent systems
- Production experience with LangChain, LangGraph, LangSmith, and AWS Bedrock
- Robust microservices and distributed, event-driven systems experience
- Hands-on in Python, Node.js, React, and cloud-native architecture on AWS
- Experience with GxP validation or FDA-regulated systems

Nice to have

- Pharma, Life Sciences, CRO, Site Network, or Healthcare background
- AWS Solutions Architect Professional or Machine Learning Specialty certification
- Experience with Strands Agents, MCP, and vector databases (pgvector, OpenSearch)

📌 Product Engineering Lead - Agentic AI (Hyderabad)
🏢 Maxis Clinical Sciences
📍 Hyderabad