Senior Engineering Manager

We are looking for an experienced Senior Engineering Manager - Agentic AI Platforms to lead the development, scalability, and execution of next-generation AI-driven enterprise platforms powered by Agentic AI, Generative AI, LLMs, intelligent automation, and autonomous workflows. This role requires strong expertise in AI platform engineering, distributed systems, scalable backend architecture, engineering leadership, and enterprise AI ecosystems. The ideal candidate should have hands-on experience building scalable AI platforms and leading high-performing engineering teams across AI-first product environments. The candidate will work closely with Product, AI/ML, Platform Engineering, Data Science, and Architecture teams to build enterprise-scale AI systems and intelligent automation platforms.
The core responsibilities for the job include the following:
Engineering Leadership:
Lead and scale high-performing engineering teams focused on Agentic AI and enterprise AI platforms.
Drive engineering execution, technical strategy, delivery planning, and operational excellence.
Mentor Engineering Leads, Senior Engineers, and cross-functional teams.
Establish engineering best practices, architecture standards, code quality, and scalable delivery frameworks.
Agentic AI Platform Development:
Design and build scalable Agentic AI systems and enterprise AI platforms.
Drive development of: Autonomous AI agents, Multi-agent orchestration systems, AI copilots and enterprise assistants, Intelligent workflow automation platforms, Context-aware AI systems and orchestration workflows.
Build reusable AI platform capabilities supporting enterprise-scale AI adoption.
Drive AI platform scalability, reliability, observability, and operational readiness.
AI / GenAI Technical Expertise:
Strong understanding of: Large Language Models (LLMs), generative AI ecosystems, RAG architectures, Agentic AI frameworks, Prompt orchestration, Vector databases, AI orchestration frameworks, AI evaluation, and observability systems.
Collaborate closely with AI/ML and Architecture teams on platform design and enterprise AI initiatives.
Drive integration of enterprise APIs, workflows, and cloud-native AI services.
Backend and Distributed Systems:
Architect and develop scalable backend systems and distributed AI platforms.
Drive microservices architecture, event-driven systems, APIs, and cloud-native platform development.
Ensure high availability, fault tolerance, performance optimization, and scalability across AI systems.
Cross-Functional Collaboration:
Partner closely with Product, Design, AI/ML, Platform, and Business teams.
Translate business requirements into scalable technical solutions and AI workflows.
Drive sprint planning, technical roadmap execution, stakeholder communication, and delivery governance.
Requirements:
13-16 years of experience in Software Engineering / Platform Engineering / AI Engineering.
Strong experience leading engineering teams and enterprise-scale platform development.
Proven experience working on AI/ML or Generative AI-based platforms.
Deep understanding of: Distributed systems, Cloud-native architectures, Enterprise backend platforms, AI/GenAI ecosystems, and Intelligent automation systems.
Strong expertise in scalable system design and platform engineering.
Excellent stakeholder management and leadership capabilities.
Preferred Skills:
Experience with OpenAI / Anthropic ecosystems, LangChain / LangGraph, CrewAI / AutoGen / Semantic Kernel.
Experience with Python / Java / Golang, Kubernetes / Docker, Vector databases (Pinecone, Weaviate, ChromaDB, etc. ), AWS / Azure / GCP, CI/CD pipelines and DevOps practices.

Experience
13-16 yrs