Senior AI Solutions Architect Lead

Leidos • Alexandria, VA

1d

About The Position

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.

Requirements

• Active Top Secret (TS) clearance with SCI eligibility.
• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related technical discipline and 8–12 years of relevant experience OR Master’s degree in a related field and 6–10 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 GCP).
• Experience designing and delivering AI/ML solutions in enterprise cloud environments (AWS, Azure, or GCP).
• Experience integrating AI/ML capabilities into production systems using APIs and microservices architectures.
• Experience developing AI/ML pipelines including data preparation, model training, validation, and deployment.
• Experience working across cross-functional teams to deliver integrated technical solutions.
• Experience operating within SAFe or large-scale Agile frameworks supporting enterprise systems.
• Experience with system architecture design and implementation in classified environments.
• Experience developing Agentic AI solutions such as 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)
• Experience using vector databases (e.g., Pinecone, Weaviate, FAISS)
• Demonstrated experience leading and mentoring technical engineering teams.
• Strong understanding of AI/ML technologies and their application in enterprise environments.
• Strong understanding of AI/ML frameworks (e.g., PyTorch, TensorFlow) and data engineering concepts.
• Solid understanding and hands-on experience with generative AI models such as 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
• Familiarity with deployment into virtualized and containerized environments (e.g., VMware, Docker, Kubernetes)

Nice To Haves

• Active TS/SCI clearance.
• 12+ years of experience in AI solutions architecture and systems engineering.
• Experience operating within SAFe or large-scale Agile frameworks supporting enterprise systems.
• SAFe Agilist (SA) or SAFe Architect certification.
• Advanced cloud architecture certification (e.g., AWS Solutions Architect – Professional, Azure Solutions Architect Expert, Google Professional Cloud Architect).
• Experience supporting AI solutions across multi-enclave DoD environments.
• Experience implementing AI governance, model validation, and bias mitigation frameworks.
• Experience integrating AI/ML solutions with enterprise data platforms and analytics environments.
• Experience supporting AI/ML-enabled mission applications or decision-support systems.
• Experience integrating AI/ML workloads with GPU-accelerated environments and performance optimization strategies.
• Experience supporting enterprise data, analytics, and AI platform 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 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.
• Familiarity with DoD standards and policies related to AI and cybersecurity.
• Experience with cloud-based AI platforms and tools.

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.

Benefits

• Pay and benefits are fundamental to any career decision.
• That's why we craft compensation packages that reflect the importance of the work we do for our customers.
• Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement.
• More details are available here.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees