Engineering Manager - Agentic AI

As an Engineering Manager at Agentic AI, based in Gurgaon, you will play a crucial role in leading a startup pod of 78 engineers to develop an enterprise-grade Agentic AI platform and applications for recruitment processes. Your responsibilities will include owning the end-to-end delivery of Agentic AI features, being hands-on in coding (30-50%), designing agentic systems, leveraging LLMs smartly, shipping production ML/LLM workflows, MLOps & Observability, defining EVALs & quality metrics, DevOps practices, ensuring security & compliance, people leadership, and stakeholder management. Key Responsibilities: - Own delivery end-to-end for Agentic AI features, including backlog, execution, quality, and timelines - Be hands-on in coding (30-50%) to set the technical bar in Python/TypeScript, review PRs, and solve complex problems - Design agentic systems incorporating tool-use orchestration, planning/looping, memory, safety rails, and cost/perf optimization - Ship production ML/LLM workflows such as data pipelines, feature stores, retrievers, and model registries - Implement MLOps & Observability practices to automate training/inference CI/CD, monitor quality, drift, toxicity, latency, cost, and usage - Define EVALs & quality metrics, set up offline/online EVALs, and establish guardrails for task-level metrics - DevOps practices: own pragmatic infra with the team using GitHub Actions, containers, IaC, and basic K8s to maintain a healthy production environment - Ensure security & compliance by enforcing data privacy, tenancy isolation, and handling PII, in collaboration with the Security team - Lead and grow a high-trust team through recruitment, coaching, and establishing team rituals - Collaborate with Product/Design/Recruitment SMEs to translate business goals into roadmaps Qualifications Required: - 10+ years in software/ML with 4+ years leading engineers in high-velocity product teams - Experience in building and operating LLM-powered or ML products at scale - Strong coding skills in Python, Java, and TypeScript/Node, along with solid system design and API fundamentals - Exposure to frontend technologies like React, Angular, and Flutter, as well as SQL databases like Postgres and MariaDB - Practical experience in MLOps, LLM tooling, observability & EVALs, DevOps practices, and AI SDLC tools - Product mindset focusing on measuring outcomes and making data-driven decisions Additional Company Details (if present): The company is focused on developing an enterprise-grade Agentic AI platform and applications for recruitment processes, aiming to ship fast, measure rigorously, and scale responsibly.,