SME AI Solutions architect Lead

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 Solutions Architect Lead 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 and implement end-to-end AI architectures that meet mission, performance, and security requirements.
• Define system topology, data flows, model serving patterns, and integration points using scalable frameworks.
• Select and configure AI platforms and model orchestration tools to ensure high availability and low latency.
• Collaborate with software, data, and platform engineers to validate architecture decisions and optimize deployment patterns.
• Ensure compliant, production-grade implementation of AI capabilities across classified and unclassified environments.
• Lead a team of 8-15 direct reports, providing mentorship and guidance to enhance team performance.
• Develop and maintain a System Engineering Plan (SEP) to manage all systems architecture aspects.
• Conduct systems engineering activities to specify, build, and maintain system engineering designs.
• Manage requirements and maintain a system requirements management environment.
• Support enterprise system architecture activities to define and scope the AI solutions.
• Define, document, and maintain APIs and technical standards for interoperability.
• Engineer and continuously improve the underlying infrastructure of the AI platform.
• Identify and integrate government, commercial, and open-source tools into the AI environment.
• Design and enhance user interface (UI) and user experience (UX) components of the platform.
• Implement and maintain services for production-ready AI/ML models.
• Ensure cybersecurity compliance and maintain cybersecurity architecture for the AI system.
• Perform site reliability engineering to maintain a reliable and efficient AI platform.

Basic Qualifications:

• Active Top Secret (TS) clearance with SCI eligibility.
• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, 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 systems engineering and AI and/or data intelligence architectures.
• Experience architecting and deploying enterprise AI/ML solutions in cloud environments (AWS, Azure, or Google Cloud Platform).
• Experience designing AI/ML pipelines including data preprocessing, model training, validation, and production deployment.
• Experience integrating AI/ML solutions into DevSecOps and CI/CD environments.
• Experience implementing scalable model serving architectures and API-based AI services.
• Demonstrated experience leading and mentoring technical engineering teams.
• Strong understanding of AI/ML technologies and their application in enterprise environments.
• Experience with system architecture design and implementation in classified environments.
• 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 solutions architecture and systems engineering.
• SAFe Agilist (SA) or SAFe Architect certification.
• Experience operating within SAFe or large-scale Agile frameworks supporting enterprise systems.
• Master's degree in a relevant field.
• Experience supporting AI architectures across multi-enclave DoD environments.
• Experience designing enterprise AI governance, model risk management, and bias mitigation frameworks.
• Experience integrating AI/ML workloads with GPU-accelerated environments and performance optimization strategies.
• Experience supporting enterprise data, analytics, and AI platform modernization initiatives.
• Advanced cloud architecture certification (e.g., AWS Solutions Architect - Professional, Azure Solutions Architect Expert, Google Professional Cloud Architect).
• 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, Google Cloud Platform Vertex AI
• Hands-on GPU programming experience for ML workloads using CUDA, PyTorch, or TensorFlow, including optimization for performance and efficiency.
• Familiarity with DoD standards and policies related to AI and cybersecurity.
• Experience with cloud-based AI platforms and tools.

Relevant certifications in AI/ML or systems engineering are a plus.

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 9, 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.