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 Senior AI Integration 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:

• Implement AI components within existing systems and workflows to support operational use.

• Design and manage interfaces and APIs that connect AI models to enterprise platforms.

• Ensure reliable production performance by monitoring data flows, validating system interactions, and resolving integration issues.

• Collaborate with software, data, and platform engineering teams to maintain stable and efficient AI deployment across the enterprise.

• Prepare, maintain, and execute a System Engineering Plan (SEP) for managing all systems architecture and system engineering related aspects of the program.

• Conduct systems engineering activities required to specify, build, and maintain system engineering designs for the System.

• Design, prepare, and document systems engineering and cybersecurity artifacts for the System.

• Establish and maintain an existing System Requirements management environment and associated system requirements management process for the System.

• Support the Government in recommending and conducting enterprise system architecture activities to fully define and scope the System.

• Define, document, maintain, and promulgate APIs and technical standards for using and interoperating within and outside the System.

• Design, engineer, integrate, and continuously improve the underlying infrastructure of the System.

• Identify, prepare, track, secure, and integrate government, commercial, and open-source tools and services into the System.

• Design, architect, engineer, and continuously improve the user interface (UI) and user experience (UX) components of the Platform.

• Design, build, and maintain services and products to effectively make production-ready AI/ML models accessible for customer use.

• Design, architect, engineer, and continuously improve all aspects of cybersecurity elements of the System.

• Perform site reliability engineering to build and maintain a reliable, scalable, and efficient System.

Basic Qualifications:

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

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Artificial Intelligence, or related technical discipline and 8–12 years of relevant experience OR Master’s degree in a related field and6–10 years of relevant experience.

• At least one of the following foundational qualification pathways consistent with DoD 8140 requirements:

• Current DoD 8570/8140 baseline certification appropriate for Intermediate/System Administrator roles (e.g., Cloud+, GICSP, GSEC, or SSCP),

• Offerings listed in the DoD 8140 Training Repository,

• Demonstrated equivalent training and experience qualifying under DoD 8140 foundational qualification alternatives.

• Experience with designing and managing interfaces and APIs for AI models.

• Proficiency in monitoring data flows, validating system interactions, and resolving integration issues.

• Experience with cloud environments, network, data storage, logging, and auditing functions.

• Knowledge of cybersecurity policies and requirements, including NIST security controls and Zero Trust compliance.

• Experience with Dev Sec Ops/Factory functions and mission spaces.

• Ability to design and maintain system engineering and cybersecurity artifacts.

• 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 Lang Chain, Lang Graph, CrewAI, A2A, MCP, or Auto Gen.

• 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.

• SAFe Agilist (SA) or related SAFe certification.

• 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 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 Lang Smith, 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, Py Torch, or Tensor Flow, 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 $107,900.00 - $195,050.00

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.