Senior AI and Large Language Model (LLM) Engineer

LOCATION: Bethesda, Maryland (On-site / Not-remote)Overview

We are seeking an experienced AI/LLM Engineer to lead the design, customization, and integration of large language models (LLMs) into biomedical research workflows and information retrieval systems. We are looking for someone with hands-on experience training, fine-tuning, augmenting, and deploying LLMs in production environments, ideally within biomedical or life sciences domains. The role is product-oriented and forward-looking, focused on building the next generation of AI-enabled search, retrieval, and knowledge discovery tools.

This role serves as a subject matter expert (SME) across multiple product and engineering teams. The selected candidate will help define, architect, and implement LLM-driven capabilities across a portfolio of NCBI services. The position requires strong technical depth, sound architectural judgment, and the ability to collaborate effectively within existing product and technical ecosystems.

This is a hands-on, build-oriented role with strategic influence. The candidate must be capable of guiding both what gets built and how it gets built.

Only serious candidates accepted - we are not seeking candidates that have recently graduated with a masters degree in the past 1-2 years.

We are seeking candidates with at least 3+ years experience doing this work after your last degree.

Key Responsibilities

• Serve as the AI/LLM subject matter expert across product and engineering teams.

• Collaborate with product managers and technical leads to define AI-enabled capabilities and define the use of LLMs across NCBI platforms (e.g., PubMed and related systems).

• Develop and implement retrieval-augmented generation (RAG) systems integrating LLMs with large-scale biomedical datasets.

• Provide architectural guidance on model selection, domain adaptation, evaluation strategies, and deployment approaches.

• Improve model grounding, factual accuracy, and scientific reliability in domain-sensitive applications.

• Support engineering teams in productionizing AI solutions, ensuring scalability, performance, and maintainability.

• Evaluate emerging LLM techniques and recommend practical adoption strategies aligned with organizational priorities.

Required Qualifications

• 3+ years of hands-on experience working with large language models (training, fine-tuning, augmentation, or deployment).

• Demonstrated experience integrating LLMs into production systems (e.g., semantic search, RAG pipelines, domain-specific QA).

• Strong experience in ML system architecture and scalable deployment.