Role overview
Hi,
Hope you are doing good!
We have a
Full-time
opportunity for you as
Data Scientist
@
**Multiple Locations Across USA
Role: Data Scientist
Locations: Bellevue, WA / Richardson, TX / Austin, TX / Houston, TX / Tempe, AZ / Phoenix, AZ / Denver, CO / Charlotte, NC / Raleigh, NC / Alpharetta, GA / Tampa, FL / Palm Beach, FL / Sunnyvale, CA / Hartford, CT / New York, NY / Bridgewater, NJ / Washington, VA
Type of Hiring: FTE
Job Description:**
Client seeking a hands-on Gen AI / Agentic AI Lead 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.
What you'll work on
- 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, GCP 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.
What we're looking for
- 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).