Engineering Manager - AI & ML

Job Title : Engineering Manager (Agentic AI & Full-Stack Systems)Locations : Nagar) In-Office (4 Days a Week)Experience : 8+ Years (with 2+ years in Engineering Leadership)Technical Focus : Generative AI, Agentic AI, LLM Orchestration, Graph RAG, Full-Stack ArchitectureRole Overview : Why This Role Exists :We are an agentic AI platform for financial services, currently experiencing double-digit monthly growth and serving large enterprises across the US, Europe, and APAC. As an Engineering Manager, you will not just "manage" people; you will be the technical architect and cultural anchor for our engineering team.You will spend roughly 40-50% of your time in the trenches writing code, architecting Agentic workflows, and reviewing PRs while the other half is dedicated to mentoring, unblocking your team, and aligning technical roadmap with our business goals. Design and lead the development of complex, autonomous AI agents capable of multi-step reasoning and inference-time decision-making.RAG & Knowledge Strategy : - Oversee the implementation of Graph RAG and advanced knowledge graphs to ensure our agents have high-fidelity context with zero hallucinations.Full-Stack Ownership : - Manage a tech stack consisting of TypeScript (APIs), React/Next.js (Frontend), and Python (AI/ML core). Infra & Scaling : - Partner with the DevOps team to ensure our Kubernetes clusters on AWS are optimized for the low-latency requirements of Voice and Chat AI.Actively lead the recruitment of top-tier talent (Mid to Senior engineers) to build a world-class engineering hub in Gurgaon and Chennai.- Manage engineering sprints with minimal meetings, maximizing "deep work" zones for the team while ensuring on-time delivery of enterprise features.Full-Stack Mastery : Extensive experience in Node.js/TypeScript and React. You should be able to debug a frontend hydration issue as easily as a backend memory leak.- GenAI Deep-Dive : Professional experience in Prompt Engineering, evaluating LLMs (open vs. closed source), and building production-grade RAG pipelines.- Solid understanding of AWS/GCP, Docker, and Kubernetes to guide the team in cost-effective scaling.Behavioral Traits : - Intrinsic Motivation : You are someone who succeeds even without structure and works hard even when no one is watching.- Low Ego : You are easy-going, friendly, and help others out.