Engineering Manager (Agentic AI)

We are looking for an experienced Engineering Manager of agentic AI to lead the design, development, and delivery of production-grade AI agents and autonomous workflows. This role is ideal for someone who has built 01 AI product, led high-performing engineering teams, and successfully deployed agentic AI systems into production. You will work closely with Product, AI/ML, Platform, and Dproduct to build intelligent systems powered by LLMs that solve real-world agentic problems at scale. The ideal candidate combines strong engineering leadership with hands-on expertise in modern AI frameworks, distributed systems, and scalable cloud architectures.
Responsibilities:
Lead and mentor a team of AI and backend engineers building agentic AI applications.
Drive end-to-end development of 01 production-ready AI product.
Architect autonomous AI workflows using modern agent frameworks and orchestration platforms.
Build scalable LLM-powered applications with high reliability, security, and observability.
Collaborate with product and design teams to define AI product strategy and execution.
Establish engineering best practices, code quality standards, testing, and CI/CD pipelines.
Design scalable backend services and APIs supporting AI-driven experiences.
Optimize inference latency, prompt engineering, retrieval quality, and AI system performance.
Implement monitoring, evaluation, and guardrails for production AI systems.
Own technical roadmap, delivery planning, hiring, and engineering excellence.
Drive architecture discussions and technology decisions across AI platforms.
Requirements:
8-13 years of software engineering experience with 2-4+ years managing engineering teams.
Proven experience leading high-performing engineering teams in product companies.
Strong experience delivering large-scale consumer-facing products.
Strong engineering leadership with a hands-on mindset.
Proven track record of building production-scale Agentic AI systems.
Passion for solving complex engineering challenges using AI.
Excellent communication and stakeholder management skills.
Ability to thrive in a fast-paced, high-growth product environment.
Agentic AI and Generative AI:
Hands-on experience building Agentic AI workflows in production.
Experience building 01 AI product from concept to scale.
Strong understanding of LLM orchestration and multi-agent architectures.
Experience with: LangChain, LangGraph, LlamaIndex, CrewAI, and AutoGen.
Strong knowledge of RAG (Retrieval-Augmented Generation), tool calling, function calling, memory management, planning and reasoning, prompt engineering, and AI evaluation.
Backend and Platform:
Strong expertise in Python (preferred) or Java.
Experience with FastAPI, Flask, or Django.
Strong API design using REST/GraphQL.
Experience designing distributed systems and microservices.
Knowledge of asynchronous processing and event-driven architectures.
AI Infrastructure:
Experience integrating OpenAI, Anthropic, Gemini, or open-source LLMs.
Hands-on experience with vector databases: Pinecone, Weaviate, pgvector, and ChromaDB.
Experience with AI observability tools such as LangSmith, Arize, or similar platforms.
Familiarity with MCP (Model Context Protocol) and AI tool integrations is a plus.
Cloud and DevOps:
Experience with AWS, GCP, or Azure.
Experience in Docker and Kubernetes, CI/CD pipelines, and monitoring and logging.
Infrastructure as Code is a plus.
Preferred Qualifications:
Experience working in B2C or consumer-facing product companies.
Strong understanding of AI safety, governance, and production best practices.
Experience scaling AI systems serving millions of users.
Experience with experimentation, A/B testing, and AI performance optimization.
Bachelor's or master's degree in computer science or a related field from a reputed institution.

Experience
9-13 yrs