Senior AI Engineer

Project overview

This senior/lead role owns the design, development, deployment, and ongoing improvement of production LLM applications and enterprise RAG pipelines, including their APIs and user interfaces. The key requirements are strong Python and FastAPI skills, Angular or Next.js with TypeScript, LangChain, LangGraph, LangSmith, RAG and vector-search expertise, and production MLOps experience. The position also calls for sound application architecture, testing and security practices, Docker and Kubernetes, and the ability to lead technical decisions and mentor engineers.

The description asks for 7–10 years in software or data engineering, including 3–4 years in AI/ML and LLM solutions; prompt evaluation, fine-tuning, and specific model-provider experience are value-added. The role is in Bengaluru and is a contract engagement; the work mode is not specified. No product or industry domain is identified, and the description lists a relevant bachelor's or master's degree as an expectation.

Responsibilities

• Deep expertise in LLM-based application development and RAG pipelines
• Proven ability to lead AI architecture decisions and mentor engineering teams
• Solid full-stack software engineering background with hands-on experience in FastAPI and Angular or Next.js
• Strong command of MLOps practices and production-grade ML deployment
• Ability to build scalable, maintainable web applications from MVP to production — with clean architecture from day one
• Excellent stakeholder communication and cross-functional collaboration skills
• Autonomous, analytical mindset with a passion for cutting-edge AI technologies
• Lead the design and development of LLM-based applications using modern AI frameworks
• Architect and maintain RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases
• Develop and orchestrate AI agents and workflows using LangChain and LangGraph
• Monitor, trace, and evaluate model performance using LangSmith
• Implement and manage vector embeddings and vector databases (e.g., Pinecone, Weaviate, ChromaDB, FAISS)

Requirements

• Python and clean software engineering practices, including SOLID and Git
• FastAPI and production REST APIs, including async endpoints, dependency injection, middleware, and OpenAPI
• Angular or Next.js frontend development with TypeScript
• Scalable, modular application architecture and separation of concerns
• REST API design, versioning, authentication, and API security
• Unit and integration testing, including pytest, Jest, or equivalent
• LLM application development with LangChain, LangGraph, and LangSmith
• LLM fundamentals and end-to-end RAG pipeline design
• Embeddings, vector databases, chunking, retrieval optimization, re-ranking, and hybrid search
• MLOps, including model versioning, ML CI/CD, monitoring, and retraining pipelines
• MLflow, DVC, Kubeflow, or comparable MLOps tooling
• Docker and Kubernetes
• Production model performance monitoring and drift detection
• Technical leadership, mentoring, and cross-functional stakeholder communication

Project details

• Start: flexible
• Remote: onsite
• Location: India, IN