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

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)

Benefits

Health and Wellness programs
Income Protection
Paid Leave
Retirement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI architecture designmodel orchestrationAPI integrationAI/ML pipelinesdata preparationmodel trainingmodel validationmodel deploymentsystems engineeringcybersecurity architecture

Soft Skills

mentorshipteam leadershipcollaborationguidancecommunicationcross-functional teamworkproblem-solvingperformance optimizationtechnical documentationinteroperability

Certifications

Top Secret (TS) clearanceBachelor's degreeMaster's degree