Generative AI Engineer (Director)

Job Description – Director AI Engineering and Architect (Hands - on Engineer)
We are seeking a highly accomplished Agentic AI Architect with 15+ years of software engineering experience and a proven track record of designing, architecting, and developing enterprise-scale Agentic AI platforms and autonomous AI workflows. The ideal candidate should possess strong programming expertise in Python or Java along with deep knowledge of Large Language Models (LLMs), LangChain, and modern AI agent frameworks.
Key Responsibilities
Architect and build enterprise-grade Agentic AI platforms and autonomous AI workflows from concept to production.
Design scalable multi-agent architectures capable of reasoning, planning, memory management, and tool orchestration.
Develop AI applications using Python or Java with a strong focus on maintainability, scalability, and performance.
Build and optimize LLM-powered solutions using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, or similar.
Design Retrieval-Augmented Generation (RAG) architectures integrating vector databases and enterprise knowledge sources.
Develop intelligent AI agents capable of tool calling, workflow automation, and complex decision-making.
Collaborate with Product, Engineering, and Data Science teams to define AI architecture and technical strategy.
Establish best practices for AI platform development, deployment, governance, observability, and security.
Mentor engineering teams and provide technical leadership on AI architecture and emerging technologies.
Required Skills & Qualifications
15+ years of experience in software engineering with strong expertise in Python or Java.
Proven experience architecting and delivering Agentic AI platforms, AI agents, or autonomous AI workflows in production.
Strong hands-on experience with Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, or equivalent.
Deep expertise in LangChain and experience with AI orchestration frameworks such as LangGraph, CrewAI, AutoGen, or LlamaIndex.
Experience designing and implementing RAG (Retrieval-Augmented Generation) solutions and integrating vector databases.
Strong understanding of prompt engineering, agent memory, tool/function calling, planning, and reasoning frameworks.
Experience building scalable, cloud-native AI applications on AWS, Azure, or GCP.
Strong knowledge of distributed systems, microservices architecture, REST APIs, Docker, and Kubernetes.
Excellent software design, architecture, and problem-solving skills.
Strong communication and stakeholder management abilities with experience leading technical architecture discussions.
Preferred Background
Bachelor's or Master's degree in Computer Science or a related field from a premier engineering institute (IIT, BITS Pilani, IIIT, NIT, IISc, or equivalent).
Prior experience working with leading product-based organizations building enterprise-scale AI platforms or AI-first products.

Work arrangement
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