Technical Director, AI Decision Systems

ABOUT DEFCON AI

RESILIENCE IN THE FACE OF DISRUPTION. DEFCON AI is an insights company that leverages artificial intelligence, mathematical optimization, data analytics, and software engineering for resilient optimization of complex systems.
In today’s dynamically changing world, DEFCON AI’s technology aligns outcomes with operational goals, better decision making, and empowers customers to anticipate assess, and mitigate the impacts of disruptions.

DEFCON AI is seeking a Technical Director, AI Decision Systems to lead the cross-functional team delivering a new AI-enabled decision-support capability for the federal government. The team spans product and design, software engineering, data architecture, applied analytics, AI solutioning, DevSecOps, cybersecurity, quality engineering, and technical transition.

This is a zero-to-one leadership role for a proven technical practitioner ready to broaden their scope. You may come from engineering, data, AI, product, design, platform, or another technical discipline. We do not expect you to be the deepest expert in every vertical. We do expect you to recognize excellent work, ask hard questions, create clarity across disciplines, and hold the system together.

You will turn mission needs, product direction, technical constraints, and delivery commitments into one coherent execution plan. You will establish technical priorities, resolve seams between teams, build an effective operating rhythm, and ensure that separate workstreams converge into a secure, explainable, and operational capability.

The right person is entrepreneurial, resourceful, and energized by the first mile. You enjoy incomplete information, emerging workflows, consequential decisions, and the opportunity to build both the system and the team delivering it. You move quickly, but you know when speed must be reinforced by testing, documentation, security, and repeatable delivery.

This is remote-first with occasional travel (up to 25% at times) to DEFCON AI HQ, customer sites, and vendor facilities as required.

Key Responsibilities

• Lead the cross-functional delivery team spanning product, design, engineering, data, AI, analytics, DevSecOps, cybersecurity, and quality.
• Own technical strategy, architecture, execution, and delivery from discovery through operational deployment.
• Translate mission needs and product priorities into clear technical plans, release objectives, and engineering decisions.
• Align software, data, AI, infrastructure, security, and quality into one integrated system.
• Build, mentor, and scale a high-performing technical organization.
• Make architecture, integration, tooling, and delivery decisions that balance speed, security, quality, and maintainability.
• Identify and resolve technical risks, dependencies, and ambiguity before they impact delivery.
• Partner effectively with customers, product leadership, and external stakeholders.
• Remain technically hands-on enough to challenge assumptions, review designs, and solve hard problems.
• Significant accomplishment in software engineering, AI/ML, data systems, analytics, DevSecOps, cybersecurity, product technology, or a comparable technical discipline.
• Experience leading complex technical efforts across multiple teams and specialties.
• Demonstrated ability to turn ambiguity into working systems and measurable outcomes.
• Strong systems thinking, communication skills, and leadership judgment.
• Experience delivering cloud-native software from concept through deployment and operations.
• US Citizenship Required.
• In scope US Secret clearance.
• Elevated security requirements apply to portions of this work and are discussed during the interview process.
• Willingness to travel up to 25% to customer sites, DEFCON AI HQ, and vendor facilities as required.

Preferred Qualifications

• Clearance: Active Top Secret.
• Experience leading a zero-to-one product, platform, or mission capability.
• Experience delivering technology in defense, intelligence, federal, or similarly regulated environments.
• Experience with AWS GovCloud, DevSecOps, CI/CD, infrastructure as code, and secure cloud delivery.
• Experience supporting RMF, ATO, accreditation, or comparable security processes.
• Experience with AI/ML, large language models, analytics, graph technologies, or data-intensive systems.
• Experience building human-in-the-loop decision-support systems and explainable AI capabilities.
• Experience partnering closely with product and design teams to deliver user-centered software.
• Experience hiring, mentoring, and organizing technical teams during rapid growth.
• Experience integrating third-party, partner, or subcontractor-delivered capabilities into a unified solution.

A Note to Candidates

You do not need to have held this exact title before to be a strong candidate. We encourage accomplished practitioners from software engineering, data, AI, analytics, product technology, DevSecOps, cybersecurity, design, or quality engineering who are ready to lead across disciplines and grow a team around an important mission.

A thoughtful cover letter will materially strengthen your application. Tell us what you have built, where your technical depth comes from, why you are ready to lead beyond your primary discipline, and how you approach a zero-to-one effort where the team, architecture, and operating model are all taking shape. Applications without a cover letter will still receive consideration, but the letter is the best opportunity to show us the judgment, motivation, and leadership potential that a résumé alone may not capture.

What Success Looks Like

• One team, one architecture, one release objective.
• Fast decisions, visible risks, and disciplined execution.
• Integrated, secure, and operational releases delivered with confidence.
• Product vision translated into real capability without losing user intent.
• Technical leaders who grow stronger and more autonomous over time.
• A system the customer can trust, operate, and sustain.

• Managing and administering your application throughout the hiring process;
• Verifying the accuracy and authenticity of application materials, including by cross-referencing information you provide against publicly available sources and proprietary databases;
• Identifying indicators of potentially fraudulent, fabricated, or materially misleading application content, including but not limited to discrepancies between submitted materials and publicly available professional profiles, geographic anomalies, and fabricated work histories.