Senior GenAI Engineer

Experience: 10+ Years (Overall IT Experience)
Role: Senior GenAI Engineer / Lead AI Engineer
Employment Type: W2 Contract / Full-Time

Job Summary

We are seeking a highly experienced Senior Generative AI Engineer with 10+ years of overall IT experience and strong hands-on expertise in developing, deploying, and scaling enterprise-grade Generative AI and Agentic AI solutions.

The ideal candidate should have extensive experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, AI agents, cloud platforms, and MLOps.

Key Responsibilities

• Design, develop, and deploy enterprise-grade Generative AI and Agentic AI applications.

• Build and optimize LLM-powered applications using GPT, Claude, Gemini, Llama, and other open-source models.

• Develop advanced RAG pipelines using LangChain, LlamaIndex, and vector databases.

• Implement multi-agent AI systems using LangGraph, CrewAI, and AutoGen.

• Develop AI-powered chatbots, virtual assistants, and intelligent automation solutions.

• Integrate LLMs with enterprise applications using REST APIs, FastAPI, and microservices.

• Implement prompt engineering, fine-tuning, embeddings, and semantic search techniques.

• Design and deploy scalable AI solutions on AWS, Azure, or Google Cloud.

• Build CI/CD pipelines and implement LLMOps/MLOps best practices.

• Optimize LLM performance, latency, token consumption, and operational costs.

• Implement AI security, governance, guardrails, and responsible AI practices.

• Collaborate with architects, data scientists, product managers, and business stakeholders.

Required Qualifications

• 10+ years of overall IT/software engineering experience.

• 3+ years of hands-on AI/ML or Generative AI experience, including production GenAI implementations.

• Strong Python development experience.

• Proven experience building production-ready LLM and RAG applications.

• Hands-on experience with Agentic AI frameworks such as LangGraph, CrewAI, or AutoGen.

• Experience integrating vector databases and enterprise data sources.

• Strong understanding of cloud-native architecture and microservices.

• Experience deploying AI applications using Docker and Kubernetes.

• Knowledge of LLM evaluation, observability, security, and performance optimization.

• Excellent communication, problem-solving, and technical leadership skills.

Preferred Qualifications

• Experience designing enterprise-scale Agentic AI solutions.

• Knowledge of Model Context Protocol (MCP).

• Experience with multimodal AI (text, image, audio, and video).

• Experience implementing AI governance and responsible AI frameworks.

• Knowledge of advanced RAG architectures, GraphRAG, and knowledge graphs.

• Experience with distributed systems and high-performance AI infrastructure.

Mandatory Skills

Python | Generative AI | LLMs | RAG | LangChain | LangGraph | Agentic AI | Vector Databases | AWS/Azure/Google Cloud Platform | FastAPI | Docker | Kubernetes | MLOps