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About the role
About the Role (Remote | Full-time | ₹28L – ₹55L/year) We're building AI systems that don't just respond — they reason, plan, and act. As Engineering Manager for AI & Agentic Systems, you'll lead a team of engineers building agentic applications powered by modern LLMs, multi-agent orchestration networks, and MCP (Model Context Protocol) integrations that connect AI to real-world tools and data. You'll balance hands-on technical leadership with people management — setting technical direction, unblocking your team, and ensuring what ships is production-grade, reliable, and scalable. If you love building intelligent systems and growing the engineers who build them, this role is for you. What You'll Do Technical Leadership Set the architectural direction for agentic AI systems — multi-step reasoning pipelines, autonomous task agents, and tool-using LLM workflows using frameworks like LangGraph, AutoGen, or CrewAI Guide the design and maintenance of MCP (Model Context Protocol) servers and clients connecting LLMs to internal tools, APIs, databases, and external services Oversee RAG pipelines and vector search infrastructure (pgvector, Pinecone, Weaviate) to ensure AI responses are grounded, accurate, and cost-efficient Drive technical decisions on foundation model selection and integration (Anthropic Claude, OpenAI, Gemini, and open-source models like Llama and Mistral) Lead root-cause investigations for complex AI production issues — prompt failures, agent loops, latency, and cost regressions Review architecture and code for scalable web and backend systems built on React.js, Node.js, Python, and serverless AWS Lambda workloads People & Team Management Hire, mentor, and grow a team of engineers working on agentic AI and full-stack systems Run design reviews, pair programming sessions, and 1:1s to raise the bar on code quality and technical judgment Own sprint planning, prioritization, and delivery timelines in partnership with product stakeholders Foster a culture of experimentation and rigor — balancing fast iteration on AI systems with production reliability Represent the team's technical roadmap to senior leadership and cross-functional partners What You Bring 5+ years of hands-on software engineering experience, including 1–2+ years in a technical leadership or people management role Strong hands-on background with React.js, Node.js, and/or Python Experience building with LLM APIs and prompt engineering (tool calling, structured outputs) Proven experience deploying and scaling serverless workloads on AWS Lambda AWS Certification (Solutions Architect, Developer, or equivalent) Deep understanding of agentic AI concepts — planning loops, memory, tool use, and multi-agent coordination Track record of mentoring engineers and driving technical decisions across a team Bachelor's degree or equivalent in Computer Science or related field Bonus Points Direct experience building or consuming MCP servers Hands-on with LangChain, LangGraph, AutoGen, or CrewAI Familiarity with RAG architectures and vector databases Experience with AI observability tools (LangSmith, Arize, Helicone) Experience with open-source model hosting (Ollama, vLLM, HuggingFace) Prior experience managing a distributed/remote engineering team Skills: MCP · Agentic AI · LangGraph · RAG · LLM APIs · Prompt Engineering · React.js · Node.js · Python · AWS Lambda · Vector Databases · Serverless · Engineering Management · Technical Leadership