1 month ago
Hanover, MD, USASenior
Base Salary
$195k - $250k/yr
Responsibilities
- Design, build, and deploy AI systems by integrating machine learning models into production software.
- Develop RAG applications, including document ingestion, chunking, embeddings, vector or hybrid search, reranking, and retrieval evaluation.
- Fine-tune and adapt open-weight language models using methods such as LoRA, QLoRA, and supervised fine-tuning, and benchmark results.
- Host and serve models on GPU infrastructure while managing sizing and quantization tradeoffs.
- Deploy AI capabilities in disconnected and classified environments, including transferring models, containers, and dependencies across air gaps and supporting ATO.
- Build clearance-, compartment-, and need-to-know-aware access controls for retrieval pipelines.
- Create LLM evaluation, guardrail, red-team, hallucination measurement, and prompt-injection defense capabilities.
- Build document ingestion pipelines for large unstructured collections with parsing, OCR, metadata tagging, and classification-marking preservation.
- Translate mission requirements into AI architectures and recommend prompting, RAG, fine-tuning, or agent-based approaches.
- Lead technical work across engineering, security, and mission teams and explain AI capabilities and limitations to technical and nontechnical audiences.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field, or an equivalent combination of education and relevant experience.
- At least 5 years of professional experience in software engineering, machine learning engineering, or data engineering.
- At least 2 years designing, building, and deploying LLM or machine learning applications used by real operational or business users.
- Active TS/SCI security clearance with polygraph.
- Demonstrated experience building and deploying at least one production RAG application.
- Experience fine-tuning or adapting open-weight LLMs and measuring results against a defined benchmark.
- Experience serving models with GPU infrastructure, including vLLM, TGI, NVIDIA Triton, or similar technologies.
- Proficiency in Python, an LLM orchestration framework, Docker, and Kubernetes.
- Knowledge of LLM fundamentals, RAG patterns, open-weight model ecosystems, model licensing and provenance, and AI security and compliance frameworks.
- Preferred experience with Intelligence Community, DoD, or Federal customers and classified cloud or Government-owned GPU environments.
- Preferred experience with agentic workflows, Model Context Protocol, MLOps or LLMOps, ATO packages, Government AI platforms, and AI adoption coaching.
Benefits
- Health, dental, and vision insurance.
- Paid time off and holidays.
- Retirement benefits including 401(k) matching.
- Educational reimbursement.
- Parental leave.
- Employee stock purchase plan.
- Tax-saving options.
- Disability and life insurance.
- Pet insurance.
- Hybrid or modern office environment in Hanover, Maryland, with a schedule of 5 days per week and 8 hours per day.
- Posting is open until filled; the original posting date is 10/12/2026.
Tech Stack
Categories
About Amentum
Amentum provides engineering, operations and maintenance, logistics, and mission support services to U.S. federal agencies and allied governments, including defense and energy programs. Its business centers on large, long-term government contracts spanning defense, space, nuclear cleanup, and infrastructure, with program management and technical services at the core. Headquartered in Chantilly, Virginia, it was formed in 2020 from the spinoff of AECOM’s Management Services division.