Senior 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 improvementhelping 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.

• Bachelors degree in Computer Science Artificial Intelligence Data Science Engineering or related technical discipline and 812 years of relevant experience OR Masters degree in a related field and 610 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 planningexecutionreflection 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)

Preferred Qualifications:

• 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.

• Relevant certifications in AI/ML or systems engineering

If youre looking for comfort keep scrolling. At Leidos we outthink outbuild and outpace the status quo because the mission demands it. Were not hiring followers. Were recruiting the ones who disrupt provoke and refuse to fail. Step 10 is ancient history. Were already at step 30 and moving faster than anyone else dares.

Original Posting:

Pay Range:

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.