Senior AI and Large Language Model (LLM) Engineer

Black Canyon Consulting•Bethesda, MD

8d•Onsite

About The Position

We are seeking an experienced AI/LLM Engineer to lead the design, customization, and integration of large language models into biomedical research workflows and information retrieval systems. This hands-on, product-oriented role focuses on building AI-enabled search, retrieval, and knowledge discovery tools, with strategic influence over what is built and how it is built. The role serves as a subject matter expert across product and engineering teams, helping define, architect, and implement LLM-driven capabilities across a portfolio of NCBI services, including PubMed and related systems. The selected candidate will bring technical depth, architectural judgment, and the ability to collaborate within existing product and technical ecosystems. Candidates should have at least three years of relevant experience after their last degree; recent master's graduates are not being sought. The position is on-site in Bethesda, Maryland and is not remote. The organization offers a competitive salary commensurate with experience and location, along with a benefits package that includes medical, dental, and vision coverage, a 401(k) plan with employer contribution, paid holidays, vacation, and tuition reimbursement.

Requirements

At least 3 years of hands-on experience working with large language models, including training, fine-tuning, augmentation, or deployment.
Demonstrated experience integrating LLMs into production systems, such as semantic search, RAG pipelines, or domain-specific question answering.
Strong experience in machine-learning system architecture and scalable deployment.
Proven ability to work cross-functionally with product and technical teams.
Experience serving as a technical subject matter expert guiding multi-team initiatives.
Strong programming skills in Python.
Experience with modern machine-learning frameworks such as PyTorch or Hugging Face, and retrieval infrastructure such as embeddings and vector databases.
At least 3 years of relevant experience after the candidate's last degree.

Nice To Haves

Experience building LLM-based systems for biomedical research or life sciences.
Familiarity with large scientific corpora, biomedical ontologies, structured knowledge bases, or biological datasets.
Experience developing generative AI systems for DNA, RNA, or protein sequence analysis.
Background in bioinformatics, computational biology, or related disciplines.
Experience improving factual grounding and reducing hallucinations in scientific or regulated environments.

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 the use of LLMs across NCBI platforms, such as PubMed and related systems.
Develop and implement retrieval-augmented generation (RAG) systems that integrate 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.