Senior AI/ML Engineer

Leidos; Huntsville (TN); On-site; USD 108,000 - 195,000; Full time

Job summary

Leidos Defense Systems Sector seeks a Senior AI/ML Engineer to integrate LLMs, VLMs and mLLMs into existing software products, leading the design and governance of agentic AI solutions across multidisciplinary teams.

The role requires DoD Secret clearance, a CS/DS/ML degree with 8+ years in AI/ML, and hands-on experience with Python and major ML frameworks. You will own deployment, testing, and cross‑functional collaboration for secure, compliant solutions.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, or related field and 8+ years of experience.
• 5+ years of relevant experience with AI/ML, including hands-on production integration of LLMs/VLMs
• Proven track record managing agentic AI systems through a full lifecycle
• Strong experience with agentic frameworks and patterns (MCP, tool/function calling, etc.)
• Familiarity with model documentation practices and AI governance requirements in regulated environments
• Proficiency with Python and ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers)
• Experience with prompt engineering and evaluation methodologies for generative AI
• Understanding of deployment practices (containerization, APIs, CI/CD, versioning for ML/agentic systems)
• Ability to lead the development of technical solutions for AI/ML or agentic systems and mentor other team members
• Strong written and verbal communication skills

Responsibilities

• Lead the integration of LLMs, VLMs, and mLLMs into existing software products and platforms
• Design and execute fine-tuning strategies for pretrained models (LoRA, QLoRA, RLHF/DPO)
• Architect agentic AI solutions: agent/skill design, MCP tool/server integrations, and multi-agent orchestration workflows
• Set organizational standards for prompt engineering to optimize agent reasoning and output quality
• Lead the development of test harnesses, evaluation suites, and red-teaming/adversarial testing for agentic systems prior to production release
• Own end-to-end deployment and operations of agentic AI systems – CI/CD, monitoring, versioning and rollback, and lifecycle management
• Collaborate with software engineers, product owners, security, and data teams to align capabilities with product and compliance requirements
• Present architectures and lifecycle strategies to technical leadership and stakeholders

Skills

AI/ML experience

Agentic AI

Python

ML frameworks

Prompt engineering

CI/CD for ML

Leadership

Communication

DoD clearance

Education

Bachelor’s degree in CS/DS/ML

Tools

MCP framework

Tool/Function calling

MLflow

Vector databases

RAG architectures

Job description

Looking for an opportunity to make an impact?

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers’ success. We empower our teams, contribute to our communities, and operate sustainably. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community. Our Mission, Vision, and Values guide the way we do business.

Your greatest work is ahead!

Leidos’ Defense Systems, Advanced Sensors and Protective Technologies Portfolio is seeking a talented Senior AI/ML Engineer to integrate generative AI and agentic AI systems into existing software products. Working within a multidisciplinary team, this role spans the evaluation and integration of large language models (LLMs), vision-language models (VLMs), and multimodal LLMs (mLLMs), as well as the design and governance of agentic AI solutions.

The Advanced Sensors and Protective Technologies portfolio develops and evaluates EO/IR sensor systems and protective capabilities that enhance threat detection, survivability, and mission effectiveness. This includes safeguarding mission‑critical systems through advanced microelectronic hardware assurance to ensure components remain trusted and secure. We advance sensor system technologies and hardware assurance through real‑world testing, modeling and simulation, and performance analysis to support the transition of emerging capabilities into operational systems.

If this sounds like the kind of environment where you can thrive, keep reading!

Leidos Defense Systems Sector provides a diverse portfolio of systems, solutions, and services covering land, sea, air, space, and cyberspace for customers worldwide. Solutions for Defense include enterprise and mission IT, large-scale intelligence systems, command and control, geospatial and data analytics, cybersecurity, logistics, training, and intelligence analysis and operations support. Our team is solving the world’s toughest security challenges for customers with "can’t fail" missions.

Primary Responsibilities.

• _Lead the integration of LLMs, VLMs, and mLLMs into existing software products and platforms_
• Design and execute fine-tuning strategies for pretrained models (LoRA, QLoRA, RLHF/DPO)
• Architect agentic AI solutions: agent/skill design, MCP tool/server integrations, and multi-agent orchestration workflows
• Set organizational standards for prompt engineering to optimize agent reasoning and output quality
• Lead the development of test harnesses, evaluation suites, and red-teaming/adversarial testing for agentic systems prior to production release
• Own end-to-end deployment and operations of agentic AI systems – CI/CD, monitoring, versioning and rollback, and lifecycle management
• Collaborate with software engineers, product owners, security, and data teams to align capabilities with product and compliance requirements
• Present architectures and lifecycle strategies to technical leadership and stakeholders

Basic Qualifications.

• Must be able and willing to obtain and maintain a DoD Secret Clearance (U.S. Citizenship required)
• Bachelor’s degree in Computer Science, Data Science, Machine Learning, or related field and 8+ years of experience.
• 5+ years of relevant experience working with AI/ML, including hands-on production integration of LLMs/VLMs
• Proven track record managing agentic AI systems through a full lifecycle
• Strong experience with agentic frameworks and patterns (MCP, tool/function calling, etc.)
• Familiarity with model documentation practices (model cards, versioned model registries) and AI governance requirements in regulated environments
• Proficiency with Python and ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers)
• Experience with prompt engineering and evaluation methodologies for generative AI
• Understanding of deployment practices (containerization, APIs, CI/CD, versioning for ML/agentic systems)
• Ability to lead the development of technical solutions for AI/ML or agentic systems and mentor other team members
• Strong written and verbal communication skills

Preferred Qualifications.

• Active DoD SECRET clearance or above.
• Experience applying mLLMs and VLMs
• Experience with MLOps/AgentOps tooling (MLflow, etc.)
• Familiarity with vector databases and RAG architectures
• Experience fine-tuning transformer-based models
• Experience with cloud/government cloud environments (AWS, Azure, GovCloud, IL levels)
• Experience presenting technical strategies to leadership or customers

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:

September 14, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $107,900.00 - $195,050.00

The Leidos pay range for this job level is a general guideline onlyand 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.