GenAI Scientist

Description

Open to remote candidates - but must work EST hours.

Our client, a nationally-recognized transportation and logistics company seeks a GenAI Scientist to build and enhance enterprise-grade conversational AI and document intelligence capabilities. The role will develop RAG pipelines, integrate and optimize LLMs, and deliver scalable APIs and microservices on cloud infrastructure. The work will support knowledge discovery, decision support, and secure integration with enterprise systems to drive measurable business outcomes.

We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $75.00 to $85.00/hr. w2

Responsibilities

• Enhance and maintain an enterprise AI chat and document intelligence platform.
• Develop and optimize RAG pipelines and LLM integrations.
• Build backend APIs and AI tools for scalable, multi-team use.
• Collaborate with business teams to translate document and data needs into AI solutions.
• Support production deployments with monitoring, logging, and performance optimization.
• Design microservices-based, production-ready AI solutions.
• Integrate AI solutions with corporate systems including OAuth, LDAP, and cloud services.

Experience Requirements

• 2+ years of experience in NLP, AI, or LLM-based development.
• Strong experience building APIs and production AI systems.
• Familiarity with RAG architectures, embeddings, and semantic search.
• Experience deploying AI solutions in cloud environments.
• Proficiency with Python and JavaScript or TypeScript.
• Hands-on work with LLMs, LangChain, vector search, and NLP libraries.
• Backend experience with FastAPI, Node.js, or Express.
• Cloud and DevOps experience with AWS services, Docker, Kubernetes, and CI/CD.
• Experience with MongoDB and vector databases.
• Experience with MLOps, microservices, and enterprise authentication systems (preferred).
• Knowledge of advanced NLP techniques and observability tooling (preferred).

Education Requirements

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, Linguistics, or a related field.
• Master’s or PhD in a related field (preferred).