Director Of Engineering - Intelligence Platform & Applications

Overview

Lead the Intelligence Pod at Truveta's India Development Center in Hyderabad, owning the technical direction and delivery of agentic AI and platform systems that learn from large healthcare data and deliver insights through automation and reasoning.

What you'll do

• Lead the team's technical direction: define and own the technical vision, architecture and engineering roadmap for the pod's area, such as agentic workflows, knowledge curation and retrieval, structured reasoning and automated evaluation.
• Make pragmatic trade-offs between innovation, performance, cost and reliability.
• Architect agentic AI systems: design multi-agent workflows with frameworks such as LangChain/LangGraph, AutoGen or CrewAI that combine reasoning, planning, memory and tool use.
• Apply strong context engineering, agent harnesses and deterministic guardrails so long-running agents stay reliable.
• Use interoperability protocols such as MCP, A2A and Agent Skills to build goal-driven systems that work with other agents and services.
• Use observability and evaluation tools such as LangSmith to drive continuous improvement.
• Drive knowledge curation and retrieval strategy: oversee design of retrieval-augmented generation (RAG) pipelines, knowledge graphs built from unstructured documents, embedding strategies and vector stores (e.g., FAISS, Pinecone, Chroma, Azure AI Search).
• Build and develop the team: hire, mentor and coach engineers, set a high bar for engineering quality, and build a culture of ownership and fast, thoughtful iteration.
• Partner closely with product, data and engineering counterparts across time zones.
• Champion responsible AI: ensure systems reflect ethical AI principles and meet privacy, security and regulatory expectations for healthcare data.
• Build in agent security (defenses against prompt injection and tool poisoning, sandboxing, and agent identity with least-privilege access) and human-in-the-loop safeguards against automation bias in clinical settings.
• Stay ahead of new AI architectures, agentic frameworks and approaches to reasoning and retrieval, and help the team adopt new ideas thoughtfully.

What you'll need

• 8+ years of experience building and deploying scalable, production-ready ML systems in a collaborative engineering environment.
• 2+ years in a technical lead or similar role, including setting technical direction and mentoring engineers.
• A track record of taking complex ML or AI systems from concept to production with measurable impact.
• Deep, hands-on proficiency with agentic AI frameworks (e.g., LangChain/LangGraph, AutoGen, CrewAI) and a working understanding of interoperability protocols such as MCP, A2A and Agent Skills.
• Experience building production agent harnesses with guardrails and context engineering.
• Experience designing and operating semantic search systems with knowledge graphs and/or RAG, vector databases and embeddings (FAISS, Pinecone, Chroma, Azure AI Search or similar).
• Strong expertise in agentic evaluation, including designing metrics, evaluators or reward models for continuous improvement, and evaluating agents at the agent and trajectory level.
• Strong software engineering fundamentals, with expert proficiency in Python and experience designing scalable systems in modern cloud environments (Azure, AWS or GCP).
• Excellent communication skills, including explaining technical trade-offs clearly to engineers, product partners and leadership, and working effectively across time zones and geographies.
• B.S. or M.S. in Computer Science, Artificial Intelligence or a related technical field.

Nice to have

• Experience with healthcare, life sciences or other regulated data (e.g., EHR, claims, clinical text), including privacy and compliance considerations.
• Experience running ML experiments and training at scale, including distributed training, GPU optimization and inference serving.
• Experience with MLOps and LLMOps practices: CI/CD for models, observability, drift monitoring and production evaluation loops.
• Publications, open-source contributions or patents in applied ML, NLP or agentic systems.

Details

• Location: Hyderabad, India.
• Works with product, data and engineering counterparts across time zones.