Senior AI and Large Language Model (LLM) Engineer
At a glance
Senior AI Engineering role at Black Canyon Consulting. NIH-Bethesda · no salary stated · we estimate $161,745–$225,300 across the United States.
Black Canyon Consulting has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Shape LLM features with product managers and technical leads for PubMed and related NCBI services
- Build RAG systems that connect language models to large biomedical datasets
- Guide model choices, domain adaptation, evaluation and deployment across engineering teams
- Improve grounding and scientific accuracy, then help teams scale and maintain production AI systems
- Review emerging LLM methods and recommend practical uses that fit organizational priorities
What you bring
- At least three years of hands-on LLM work after your last degree, covering training, fine-tuning, augmentation or deployment
- Experience putting LLMs into production, such as for semantic search, RAG or domain-specific question answering
- Strong Python skills, plus experience with ML architecture, scalable deployment and modern ML frameworks
- Experience guiding work as a technical expert across multiple teams and partnering with product and engineering
Who this fits
This is a senior, hands-on role for someone who can guide architecture across teams while also building and deploying systems. Biomedical or life sciences experience is preferred, including work with scientific datasets or research tools. The job is on-site in Bethesda, Maryland.
From the employer
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.
- Proven ability to work cross-functionally with product and technical teams.
- Experience serving as a technical SME guiding multi-team initiatives.
- Strong programming skills in Python.
- Experience with modern ML frameworks (e.g., PyTorch, Hugging Face) and retrieval infrastructure (e.g., embeddings, vector databases).
Preferred Qualifications
- 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.
Ideal Candidate Profile
- Technically deep in LLM training, augmentation, and evaluation.
- Comfortable influencing architecture across multiple teams.
- Able to move between strategy, design, and implementation.
- Pragmatic and product-oriented.
- Capable of integrating into existing systems and elevating technical execution immediately.
- Experience with life sciences corpora.
Benefits and Salary
We attract the best people in the business with our competitive benefits package that includes medical, dental and vision coverage, 401k plan with employer contribution, paid holidays, vacation, and tuition reimbursement.
We offer a competitive salary commensurate with experience and location.
If you enjoy being a part of a high performing, professional service and technology focused organization, please apply today!