Artificial Intelligence (AI) Engineer (SWE-2)

Location: Linthicum Heights, MD

Time Type: Full time

Job Description

Leidos has a new and exciting opportunity for an AI Engineer in our Intel Sector.  Our talented team is at the forefront in Security Engineering, Computer Network Operations (CNO), Mission Software, Analytical Methods and Modeling, Signals Intelligence (SIGINT), and Cryptographic Key Management. At Leidos, we offer competitive benefits, including Paid Time Off, 11 paid Holidays, 401K with a 6% company match and immediate vesting, Flexible Schedules, Discounted Stock Purchase Plans, Technical Upskilling, Education and Training Support, Parental Paid Leave, and much more.  Join us and make a difference in National Security!  

Job Summary:

Our LOE program provides our customer's Operations organization with the best possible solutions for their mission needs. We achieve this through rapid prototyping, new development, and advanced technology research. From leading-edge visualizations to analytic development, we're always pushing the boundaries to find new and better data sources and tradecraft to answer intelligence questions. With a focus on collaboration and a fast-paced environment, our prototype development program is the ideal place to grow your skills and make a real impact. Click here to learn more about how this program “Delivers Mission Success!”

Seeking a motivated AI Engineer with a proven track record in software engineering and deep understanding of Artificial Intelligence/Machine Learning (AI/ML) techniques to support the exciting new AI and Emerging Technologies (AI&ET) mission. The engineer will work closely with mission stakeholders to capture requirements, aid in structured planning, and improve the certification process by introducing AI/ML tooling. Additionally, the engineer will use AI/ML to develop tools and techniques to include fine tuning Large Language Models (LLM) that assist in enhanced vulnerability identification and mitigation capabilities.

Job Responsibilities/Qualifications:

• Mission Focus: Collaborate closely with technical leadership to design, develop, and maintain LLM orchestration frameworks that coordinate static analyzers, retrieval-augmented generation (RAG) systems, and automated testing pipelines. Develop and optimize data preprocessing pipelines to ingest, clean, transform, and vectorize product documentation, source code, and test results for LLM consumption. Design and implement database solutions to support RAG architectures, artifact storage, audit trails, and metadata management.
• Technical Proficiency: Collaboratively work with systems engineers to architect and deploy networked AI tools within secure enclaves and conduct performance profiling, optimization, and scalability analysis of mission systems. Support security assessments and authority to operate (ATO) processes.
• Qualifications: Bachelor's degree plus five (5) 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.
• Security Clearance: Active TS/SCI with Polygraph required.
• Desirable Skills: Familiarization with RUST, Claude Code, Codex, and CI/CD.

At Leidos, the opportunities are boundless. We challenge our staff with interesting assignments that allow them to thrive professionally and personally. For us, helping you grow your career is good business. We look forward to learning more about you – apply today!

Careers.leidos.com

CONMD

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:

Pay Range:

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.