Job Description :

We are looking for an experienced Lead AI Platform Engineer to lead the design, development, and deployment of enterprise-grade Generative AI platforms. The ideal candidate will have deep expertise in LLM engineering, RAG architectures, agentic AI frameworks, and cloud-native AI deployments, with a proven track record of building scalable, production-ready AI systems and leading high-performing engineering teams.

Key Responsibilities :

- Lead the architecture, design, and development of enterprise-scale AI platforms powered by Large Language Models (LLMs).

- Design and implement scalable RAG (Retrieval-Augmented Generation) pipelines, vector search solutions, and AI knowledge retrieval systems.

- Build and optimize Agentic AI workflows using frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.

- Develop AI-assisted automation and rule transformation pipelines for enterprise business processes.

- Drive prompt engineering, model evaluation, inference optimization, caching, and latency improvements for production AI systems.

- Design secure, scalable, and highly available AI services deployed on cloud platforms.

- Establish best practices for AI governance, model observability, monitoring, security, compliance, and responsible AI.

- Collaborate with product, engineering, data science, and business stakeholders to define AI architecture and technical roadmaps.

- Mentor engineering teams, conduct architecture reviews, and promote engineering excellence across AI initiatives.

- Evaluate emerging AI technologies, frameworks, and foundation models to continuously improve platform capabilities.

Required Skills :

- 12 - 15 years of software engineering experience, with significant experience in AI/ML and Generative AI platform development.

- Strong expertise in LLMs, Prompt Engineering, RAG, Vector Databases, and AI application architecture.

- Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or similar orchestration frameworks.

- Advanced proficiency in Python and AI/ML development frameworks.

- Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, or similar enterprise AI platforms.

- Strong knowledge of cloud-native architectures on AWS, Azure, or Google Cloud Platform.

- Experience building scalable APIs, microservices, containerized applications, and Kubernetes-based deployments.

- Familiarity with MLOps, CI/CD pipelines, model versioning, monitoring, and AI observability.

- Strong understanding of AI security, governance, privacy, and responsible AI principles.

- Excellent leadership, stakeholder management, and technical mentoring skills.

Preferred Skills :

- Experience with fine-tuning foundation models and parameter-efficient tuning techniques.

- Knowledge of distributed systems, GPU optimization, and inference acceleration.

- Exposure to graph databases, knowledge graphs, and enterprise search platforms.

- Experience leading enterprise AI transformation programs.

Education (Mandatory) :

- Full-time B.E./B.Tech, M.Tech, MS, MCA, or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related discipline.