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.