Senior AI Engineer: Mission‑Critical LLM & Security

Leidos; Linthicum (MD); On-site; USD 108,000 - 195,000; Full time

Benefits offered by this job

Paid Time Off

11 paid Holidays

401K with 6% company match

Flexible Schedules

Discounted Stock Purchase Plans

Technical Upskilling

Education and Training Support

Parental Paid Leave

Job summary

Leidos is seeking a Senior AI Engineer to join the Intel Sector. You will design and maintain LLM orchestration frameworks coordinating static analyzers, RAG systems, and automated testing pipelines, while building data preprocessing pipelines to ingest and vectorize product documentation and code for AI workloads.

You will collaborate with mission stakeholders to capture requirements, aid in planning, and improve AI/ML tooling certification, enhancing vulnerability identification and mitigation

Qualifications

• Bachelor's degree + 8 years of relevant experience or equivalent.
• Proficiency in Python, LLM integration, and data engineering.
• Experience with static analyzers, RAG framework, and relational and vector databases.
• Familiarization with Agile, Git, Jira, and Confluence.

Responsibilities

• Design, develop, and maintain LLM orchestration frameworks coordinating static analyzers, RAG systems, and testing pipelines.
• Develop data preprocessing to ingest, clean, transform, and vectorize docs, source code, and test results for LLM use.
• Architect and deploy AI tools within secure enclaves and perform performance profiling, optimization, and scalability analysis.

Skills

Python

LLM integration

Data engineering

Static analyzers

RAG framework

Relational databases

Vector databases

Agile

Git

Jira

Confluence

Education

Bachelor's degree

Tools

Git

Jira

Confluence

Relational databases

Vector databases

Job description

Leidos is seeking a Senior AI Engineer to join the Intel Sector. You will design and maintain LLM orchestration frameworks coordinating static analyzers, RAG systems, and automated testing pipelines, while building data preprocessing pipelines to ingest and vectorize product documentation and code for AI workloads.

You will collaborate with mission stakeholders to capture requirements, aid in planning, and improve AI/ML tooling certification, enhancing vulnerability identification and mitigation