Job Description

This Department of War enterprise data and analytics program delivers mission-critical capabilities that enable leaders across the Department to make faster, better-informed decisions using trusted data at scale. Leidos Digital Modernization sector is seeking an experienced SME AI/ML Engineer to support the delivery, enhancement, and adoption of enterprise data and analytics products used across multiple DoD organizations.

In this role, you will work alongside government partners, engineers, and other industry teammates to translate operational and strategic requirements into scalable, production-ready solutions. You will contribute directly to product planning, execution, and continuous improvement—helping ensure capabilities are delivered efficiently, aligned to mission priorities, and positioned for sustained success.

This position offers the opportunity to work on a high-visibility, enterprise program at the intersection of data, analytics, and emerging AI technologies. Ideal candidates are motivated by mission impact, comfortable operating in complex stakeholder environments, and interested in building deep domain expertise while delivering capabilities with real-world national security outcomes.

Primary Responsibilities:

• Design, develop, and optimize AI and ML solutions to enhance operational and analytical capabilities within a larger enterprise level Data and AI analytics platform.

• Build and maintain data pipelines for efficient data processing and model training.

• Train and tune algorithms to improve predictive accuracy and decision-support tasks.

• Deploy models into production environments, ensuring reliability and performance.

• Identify and integrate appropriate COTS, government, and custom tools within established frameworks.

• Collaborate with cross-functional teams to ensure alignment with enterprise architecture and security requirements.

• Manage project timelines and deliverables, ensuring adherence to quality standards.

• Facilitate communication between technical teams and stakeholders to align project goals.

• Stay updated on industry trends and advancements in AI/ML technologies.

• Develop and implement best practices for model development and deployment.

• Ensure compliance with cybersecurity policies and standards throughout the project lifecycle.

• Participate in the Engineering Control Board process for major engineering milestones.

• Analyze system performance metrics and recommend improvements for efficiency and scalability.

Basic Qualifications:

• Active Top Secret (TS) clearance with SCI eligibility.

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related technical discipline and 12–15 years of relevant experience OR Master’s degree in a related field and 10–13 years of relevant experience.

• Minimum of 10 years of experience in AI/ML and/or data intelligence engineering or related fields.

• Experience developing and deploying AI/ML models using frameworks such as PyTorch, TensorFlow, or equivalent.

• Experience building and integrating data pipelines to support ML workflows.

• Experience deploying containerized AI workloads (e.g., Docker, Kubernetes).

• Experience integrating AI/ML models into CI/CD and DevSecOps environments.

• Experience implementing model evaluation, performance tuning, and lifecycle management practices.

• Proven experience in designing and deploying AI/ML models in production environments.

• Strong programming skills in languages such as Python, R, or Java.

• Experience with data pipeline construction and management.

• Excellent leadership and team management skills.

• Strong problem-solving abilities and analytical thinking.

• Strong communication and interpersonal skills.

• Experience developing Agentic AI solutions, including autonomous planning–execution–reflection loops, multi-agent collaboration and coordination, and tool usage patterns including API integration, retrieval-augmented generation (RAG), and memory/context management

• Solid understanding and hands-on experience with generative AI models including prompt engineering, chain-of-thought reasoning, and Natural Language Processing (NLP) tasks such as entity extraction, summarization, and semantic search.

• Working knowledge of Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen

• Experience using vector databases (e.g., Pinecone, Weaviate, FAISS)

• Familiarity with deployment into virtualized and containerized environments (e.g., VMware, Docker, Kubernetes)

Preferred Qualifications:

• Active TS/SCI clearance.

• 12+ years of experience in AI/ML and/or data intelligence engineering or related fields.

• SAFe Agilist (SA) or related SAFe certification.

• Experience operating within SAFe or large-scale Agile frameworks supporting enterprise systems.

• Experience supporting AI/ML solutions across multi-enclave DoD environments.

• Experience implementing automated model validation, bias detection, and drift monitoring frameworks.

• Experience integrating AI services into enterprise APIs and microservices architectures.

• Experience optimizing GPU-based training and inference pipelines.

• Experience supporting enterprise-scale analytics, data platforms, or AI modernization initiatives.

• Experience with cloud-based AI/ML platforms and tools.

• Familiarity with cybersecurity principles and practices.

• Experience in a government or defense contracting environment.

• Experience designing and implementing safety, guardrails, and bias-mitigation strategies for autonomous agents and multiagent systems

• Experience integrating agents with cloud-native workflows, streaming data pipelines, and real-time decision-making environments

• Familiarity with evaluation and observability tools for AI agents, such as LangSmith, OpenAI Evals, or custom telemetry systems

• Experience with AI service integration such as NIMS, Azure OpenAI, Bedrock, GCP Vertex AI

• Hands-on GPU programming experience for ML workloads using CUDA, PyTorch, or TensorFlow, including optimization for performance and efficiency.

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:

March 10, 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 $131,300.00 - $237,350.00

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.