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Leads enterprise DevSecOps platform delivery, Agile planning, technical decision-making, stakeholder briefings, vendor coordination, and cross-functional engineering alignment. Manages program finances, risks, dependencies, and compliance across classified and air-gapped environments. Partners with government customers and engineering teams to deliver secure software factory capabilities using modern CI/CD, containerization, infrastructure-as-code, and automated security practices.

Develop SysML v2 system models and architectures using Agentic AI to generate requirements, use/verification/analysis cases, and structural/behavioral designs; build plugins via the SysML v2 API; model in Cameo Enterprise Architecture (CATIA Magic); collaborate with MBSE thought leaders on cutting-edge defense projects.

Leads a team supporting Linux and Windows systems in physical and virtualized Navy lab environments. Responsibilities include infrastructure installation, provisioning, troubleshooting, hardware and software architecture planning, vulnerability remediation, DISA STIG compliance, RMF preparation, network and virtualization support, documentation, and customer assistance. The role requires collaboration across organizations, workflow leadership, and up to 10% travel.

Design, build, test, integrate, and sustain secure software for mission-critical DoD systems. Collaborate with cross-functional teams on front- and back-end features, CI/CD (Jenkins), containerization, Kubernetes, and system integration while adhering to DoD security and performance standards.

Perform systems engineering for Naval tactical applications: IT infrastructure configuration management, hardware/software integration, testing (land and at-sea), documentation, standards enforcement, user training, and support cross-functional teams to meet government security and performance requirements.

Lead and mentor a systems engineering team to design, install, maintain, and secure physical and virtual servers and network devices. Manage patching, hardening, DISA STIG updates, RMF assessments, automation, and documentation across Red Hat, Windows, and VMware environments. Serve as technical liaison, drive engineering best practices, and support customer sites with up to 25% travel.

Serves as the division’s senior AI advisor, leading the integration of generative AI, LLMs, machine learning, and intelligent data-processing capabilities into mission-critical defense software. Develops AI pipelines, dashboards, prototypes, developer tooling, and AI-augmented engineering standards. Evaluates AI-generated code for security and reliability, mentors engineering teams, supports secure classified deployments, and identifies lifecycle automation opportunities. The role is onsite in Arlington, Mount Laurel, or San Diego, with travel up to 10%.

Serves as the senior AI authority for defense software engineering, leading generative AI, LLM, machine learning, NLP, and AI automation adoption. Integrates AI models into mission-critical systems, develops intelligent data pipelines and AI-enabled interfaces, evaluates developer tooling, establishes secure AI engineering standards, and mentors engineering teams. The role also prototypes AI use cases, supports responsible AI governance, and collaborates across engineering, security, compliance, program management, and systems teams.

Supports defense technology programs by coordinating schedules, milestones, deliverables, risks, staffing, budgets, forecasts, customer communications, and cross-functional execution. The role assists with financial management, EAC development, resource planning, program reporting, PMO processes, and stakeholder coordination while developing toward independent program management responsibilities.

Serve as the strategic and technical AI advisor for a defense engineering division. Lead AI and LLM integration into mission-critical software, develop NLP pipelines and AI-enabled dashboards, prototype emerging developer tools, establish AI-augmented engineering standards, and mentor teams on generative AI workflows. Evaluate AI-generated code for security, correctness, and performance while supporting responsible AI, secure SDLC practices, and deployment in sensitive environments. Collaborate with engineering, security, compliance, program management, and chief engineering teams.