Live opening · Posted 5 days ago

Lead AI Engineer

Recro · Bengaluru, Karnataka, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 5 days ago
CompanyRecro
LocationBengaluru, Karnataka, India (On-site)
Work modeNo
SkillsPython, Docker, Kubernetes
SourceLinkedin
ListedPosted 5 days ago

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About the role

Description supplied by the original job listing.

Role Overview
We are hiring a Tech Lead - AI Engineering (7+ years experience) to provide architectural oversight, define technical standards, and guide lean AI pods toward delivery excellence. You will establish baseline practices for backend infrastructure, agentic state machines, evaluation systems, and live observability. While steering overall strategy, you will remain hands-on in architecture, system reviews, and complex production problem-solving.
Key Responsibilities
Architectural Strategy & Governance: Define and maintain production engineering standards for Python/FastAPI microservices, containerization, EKS/Kubernetes infrastructure, and API designs.
Framework & Tooling Decisions: Guide choices between established agent frameworks (LangGraph, LangChain, Strands, ADK) and custom-built components based on engineering trade-offs.
Production Excellence: Drive end-to-end reliability across agent loops, state management, tool execution, ground-truth evals, tracing, and production monitoring.
Lean Pod Enablement: Mentor senior and mid-level engineers, unblock architectural challenges, and enforce high independence within 2-person pod delivery structures.
Engineering Standards: Review code, design docs, and deployment pipelines to ensure top-tier code quality, system resilience, and production security.
Required Qualifications & Experience
Experience: 7+ years of software engineering, backend architecture, and technical team leadership experience.
Agentic AI Leadership: 3+ years of hands-on experience architecting and deploying production-grade agentic platforms and pipelines.
Technical Expertise: Master-level capabilities in Python, FastAPI, Docker, EKS/Kubernetes, distributed system debugging, and API architecture.
Lifecycle Mastery: Deep expertise in LLMOps, evaluation benchmarks (evals), ground-truth dataset creation, agent state loops, and production observability.
Leadership Capabilities: Demonstrated success driving execution in lean engineering teams with minimal guidance and high ownership.

Work arrangement
No

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