Job description

Job Title - Gen AI Consultant with Generative AI, Agentic AI Location -Alpharetta, GA, Bridgewater, NJ, Charlotte, NC, Denver, CO, Hartford, CT, Houston, TX, New York, NY, Palm Beach, FL, Phoenix, AZ, Raleigh, NC, Richardson, TX, Sunnyvale, CA, Tampa, FL, Tempe, AZ, Washington, VA Type: Fulltime Job Description: Gen AI / Agentic AI Consultant to drive the development and deployment of next-generation AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. This role is ideal for a mid-level engineer with strong technical depth, a passion for building, and the ability to lead small teams or workstreams in a fast-paced, innovation-driven environment. Required Qualifications • Bachelor’s degree in Computer Science, AI/ML, or related field. • 4 years of experience in software engineering or data science, with 2–3 years in Gen AI or LLM-based systems. • Strong Python programming skills and experience with ML/AI libraries (Hugging Face Transformers, LangChain, PyTorch). • Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search). • Familiarity with cloud platforms and Gen AI services (AWS, Azure, Google Cloud Platform). • Experience with REST API development (FastAPI, Flask) and containerization (Docker). • Solid understanding of AI governance, model safety, and prompt engineering. Key Responsibilities • Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI). • Fine-tune open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT. • Build and optimize RAG pipelines with hybrid retrieval, semantic chunking, and vector search. • Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, Google Cloud Platform Vertex AI). • Work with unstructured data (PDFs, HTML, audio, images) and multimodal models. • Implement LLMOps practices including prompt versioning, caching, observability, and cost tracking. • Evaluate model performance using tools like RAGAS, DeepEval, and FMeval. • Collaborate with product managers, data engineers, and UX teams to deliver production-ready solutions. • Mentor junior engineers and contribute to code reviews, design discussions, and best practices. Preferred Qualifications: • Exposure to agentic workflows and autonomous agents. • Experience with CI/CD pipelines and DevOps tools (GitHub Actions, Jenkins, Terraform). • Familiarity with front-end integration (React, Angular, TypeScript) and GraphQL APIs. • Knowledge of model interpretability, bias mitigation, and human-in-the-loop systems. • Experience with multimodal models and perception systems (e.g., vision + language).

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