Lead Engineer, Agentic AI Engineering

Overview

Lead the technical execution of the AI Foundations engineering team in India, delivering agentic AI systems and platforms while remaining a hands-on individual contributor.

What you'll do

• Own end-to-end delivery of agentic AI engineering workstreams, including planning, prioritisation, dependency management, and on-time, on-standard completion.
• Track progress across parallel workstreams, surface blockers early, escalate when needed, and remove obstacles for engineers.
• Maintain visibility into project health, including scope creep, technical debt, integration risks, and resource constraints.
• Coordinate with Data Scientists, product managers, and stakeholders to align requirements, timelines, and definition of done.
• Run sprint rituals, design reviews, and retrospectives that keep the team improving without unnecessary overhead.
• Act as the technical authority for agentic systems architecture within the India team, reviewing and approving significant design decisions.
• Enforce engineering standards covering coding conventions, testing, CI/CD, security and RBAC patterns, and agent harness implementation.
• Own the team's reference architectures and reusable component library, keeping them current as the agentic AI landscape evolves.
• Identify and address technical debt proactively, deciding when to refactor versus ship and communicating trade-offs to stakeholders.
• Architect and deliver complex agentic AI solutions end-to-end on frameworks such as LangGraph, AutoGen, CrewAI, and Google ADK, and platforms such as AWS Bedrock, Azure AI Foundry, Snowflake Cortex, and Databricks Mosaic AI.
• Design for MCP/A2A interoperability, agent memory systems, tool registries, and human-in-the-loop checkpoints.
• Implement agent execution harnesses with sandboxed tool execution, policy-as-code guardrails (NeMo Guardrails, Guardrails AI), and full observability via Langfuse or LangSmith.
• Build or integrate full-stack enterprise applications with OAuth2, SAML, SSO, RBAC, secrets management, audit logging, and secure API design.
• Make production-tested choices on inference infrastructure (vLLM, SGLang, TensorRT-LLM), container orchestration (Docker, Kubernetes/EKS/AKS), and data tooling (SQL, Snowflake, Databricks).
• Coach and mentor engineers across all levels on agentic AI development, platform engineering, and software engineering craft.
• Run structured technical sessions, including design reviews, architecture walkthroughs, code review standards, and knowledge-sharing forums.
• Identify team skill gaps and address them through hiring, coaching, or deliberate project assignments.
• Contribute to hiring by defining what good looks like for engineering roles and assessing candidates rigorously.
• Stay current with the agentic AI field, evaluate new frameworks, protocols, and techniques, and recommend what to adopt.
• Champion AI-enabled development practices such as code generation, automated testing, documentation tooling, and developer experience improvements.

What you'll need

• 8+ years of software engineering in production.
• 4+ years in AI/ML or agentic systems.
• At least 2 years in a technical lead or principal engineering capacity.
• Proven ability to drive delivery across a team, including owning project timelines, managing dependencies, and ensuring engineering work lands on time and to standard.
• Deep technical expertise across the agentic AI stack, including frameworks, cloud platforms, agent safety, evaluation, inference infrastructure, and full-stack enterprise integration.
• Strong Python and SQL proficiency.
• Hands-on experience with Docker and Kubernetes in production container environments.
• Demonstrated ability to set and uphold engineering standards for coding, testing, architecture, and security, and bring a team along with them.
• Excellent communication, able to represent technical decisions to senior leadership, align with business stakeholders, and coach engineers at every level.
• Passion for the agentic AI field and a habit of staying current, bringing ideas to the team and not just execution.
• Degree from IITs, NITs, BITS, or comparable, or a strong applied track record.

Nice to have

• Background in life sciences, pharma, or regulated environments.

Details

• Location: Gurgaon, India.
• Based in the India team.