
Architecture & Data Lead
DEFCON AI
Posted about 6 hours ago
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.
About the Role
This is a rare opportunity to define how data moves across the U.S. military’s logistics ecosystem.
As the Architecture and Data Lead, you will own one of the most critical integration challenges in modern DoD software: enabling data to flow reliably across platforms, classification levels, and operational environments — and transforming it into usable, decision-ready information.
You will design and build the integration platform that connects DEFCON AI’s software to the broader logistics C2 ecosystem. This includes developing adapters, common data models, translation layers, synchronization mechanisms, and classification-aware data architecture that ensure systems remain coherent from headquarters to the tactical edge.
This is a senior role combining deep technical execution and system-level architecture leadership. You will define the architecture, build key components, and guide a team of engineers and partners to deliver production-ready integrations across disconnected environments, varied data models, and multi-enclave deployments.
Key Responsibilities
Cross-Platform Integration Architecture
- Design and implement the bidirectional data layer connecting major DoD C2 platforms (Palantir and Anduril)
- Develop common data models and translation layers to resolve schema and vocabulary mismatches
- Build and validate production-grade adapters (e.g., Foundry, Lattice) in live government environments
- Advance integration concepts into fully implemented, tested system-level data flows
Data Integration & Authoritative Source Onboarding
- Own end-to-end data flow from authoritative DoD systems into and across the platform
- Lead onboarding of key data sources (logistics, personnel, maintenance, DoD data platforms)
- Extend existing government data pipelines into DEFCON production without disrupting delivery
- Coordinate with security and DevSecOps teams to enable compliant, reliable data ingestion
Classification-Aware & Cross-Domain Data Architecture
- Architect data flows across IL-5, IL-6, and tactical environments with proper segmentation
- Implement classification-aware controls (e.g., NOFORN, REL_TO) with fail-safe enforcement
- Enable “classify the data, not the network” operations across multi-enclave systems
Interoperability, Standards & Field Execution
- Align architecture with JADC2 and Service C2 interoperability standards
- Produce and maintain interface control documents (ICDs), schemas, and API contracts
- Lead technical execution at exercises: operate integrations, validate flows, and troubleshoot in real time
- Capture lessons learned and continuously improve architecture and integration design
Platform Scalability, DDIL & Modernization
- Design and implement resilient data synchronization for DDIL environments
- Enable bandwidth-aware operation, conflict resolution, and graceful degradation to low-connectivity states
- Identify and resolve data architecture bottlenecks (e.g., geospatial scaling constraints)
- Lead refactoring and modernization as systems transition into DEFCON ownership
Required Qualifications
- 10+ years of software/systems architecture experience including at least one system-of-systems integration effort delivered to production
- 5+ years of data architecture or data engineering experience on DoD, logistics, or complex-enterprise systems
- Hands on experience building production integration adapters between systems that were not designed to talk to each other
- Demonstrated experience operating across multiple classification levels (IL-4, IL-5, IL-6) or equivalent regulated multi-enclave environments.
- US Citizenship Required
- Active Secret Clearance
- Willingness to travel up to 25% to USMC sites, Defcon AI HQ, and industry vendor facilities as required
Preferred Qualifications
- Active TS/SCI Clearance
- Experience with Palantir and/or Anduril platforms in production environments
- Experience with DoD cross-domain solutions
- Experience onboarding authoritative DoD data feeds (logistics, readiness, etc.)
- Experience with geospatial data architecture (e.g., PostGIS)
- Familiarity with USMC or Service-level logistics domains
- Experience building systems for DDIL / edge environments
What Success Looks Like
- Cross-platform integrations operate successfully in live exercises, with real-time data flowing between systems
- Architecture is delivered as working, tested system-level integrations — not just concepts
- Authoritative DoD data sources are onboarded with clear lineage and governance
- Production data pipelines are extended seamlessly without disrupting existing government workflows
- The platform scales effectively, supports DDIL operations, and establishes the program’s standard data model and interfaces
What We Offer:
- A fully remote, results-based environment
- Competitive salary, bonus, and equity package
- 100% employer paid, comprehensive health insurance including medical, dental, and vision for you and your family
- Unlimited PTO, with your manager’s approval
- Flexible work environment where you manage your work day
- 14 weeks of fully-paid parental leave
Salary Range: $175,000-$225,000. This represents the typical salary range for this position based on experience, skills, and other factors.
- 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.
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