Job Description: AI / Generative AI Engineer (6+ Years)

Job Title: AI / Generative AI Engineer
Experience: 6+ Years
Location: Pune / Bengaluru / Hyderabad / Mumbai (Hybrid)
Employment Type: Full-time

Job Summary

We are seeking a highly skilled AI / Generative AI Engineer with 6+ years of experience in designing, developing, and deploying AI-powered applications. The ideal candidate should possess strong expertise in Generative AI, Large Language Models (LLMs), Agentic AI frameworks, Retrieval-Augmented Generation (RAG), and cloud-based AI platforms. The candidate will work closely with business stakeholders, solution architects, and engineering teams to build scalable and production-grade AI solutions.

Key Responsibilities

• Design, develop, and deploy Generative AI solutions leveraging LLMs and foundation models.
• Build end-to-end AI applications involving data ingestion, prompt engineering, RAG pipelines, model orchestration, and API integrations.
• Develop intelligent AI Agents and Agentic workflows using modern orchestration frameworks.
• Implement solutions using Azure OpenAI, AWS Bedrock, OpenAI APIs, and related AI services.
• Design and manage vector databases and semantic search solutions.
• Create scalable APIs and microservices to integrate AI capabilities into enterprise applications.
• Optimize LLM performance through prompt engineering, fine-tuning strategies, and evaluation frameworks.
• Implement responsible AI practices, AI guardrails, monitoring, and governance mechanisms.
• Collaborate with DevOps and MLOps teams for deployment, monitoring, and lifecycle management of AI models.
• Stay updated with the latest advancements in Generative AI, Agentic AI, multimodal AI, and LLM ecosystems.

Required Skills

Core AI & ML

• Strong experience in Python development.
• Hands-on expertise in Generative AI and Large Language Models (LLMs).
• NLP, Transformers, Embeddings, and Prompt Engineering.
• Retrieval-Augmented Generation (RAG) architecture.
• Vector Databases (Pinecone, ChromaDB, FAISS, Weaviate, etc.).

Generative AI Ecosystem

• LangChain, LangGraph.
• Agentic AI Frameworks.
• Model Context Protocol (MCP).
• OpenAI / Azure OpenAI.
• AWS Bedrock.
• Hugging Face ecosystem.

Cloud & Engineering

• Azure and/or AWS cloud platforms.
• REST APIs, FastAPI.
• Docker, Kubernetes.
• CI/CD pipelines.
• Git, GitHub/GitLab.

Data & Databases

• SQL and NoSQL databases.
• Data ingestion and processing pipelines.
• Knowledge graph and semantic search concepts.

MLOps & Governance

• Model deployment and monitoring.
• AI Guardrails and Responsible AI.
• ML lifecycle management and MLOps tools.

Preferred Qualifications

• Experience building enterprise-scale GenAI solutions.
• Knowledge of Copilot, AI Agents, and multi-agent systems.
• Exposure to BFSI domain is highly preferred.
• Experience with React, Node.js, or full-stack development is an added advantage.
• Understanding of security, compliance, and governance requirements for AI applications.