--- title: 'Data & ML Engineer at DEFCON AI' canonical: 'https://feeny.ai/job/data-ml-engineer-defcon-ai-united-states-41fshj0wx0pq' type: 'job' last_seen: '2026-09-11' --- # Data & ML Engineer at DEFCON AI - **Company:** DEFCON AI - **Location:** United States - **Work type:** remote - **Posted:** 2026-08-06 - **Last confirmed live:** 2026-09-11 - **Apply:** https://job-boards.greenhouse.io/defcon/jobs/5205466007 ## Job description ## 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 As a Data & ML Engineer you will build the data and model layer behind an AI-enabled decision-support system operating inside an accredited environment. That work covers ingestion from many source systems, resolution of incoming records against a shared data model, relevance scoring, and generation of explanations a user can act on and defend. Three characteristics make this a substantial technical challenge. The incoming data is predominantly low-signal, which means a model can report strong overall accuracy while failing on the cases that matter most. Every output must remain traceable to the underlying sources, because a person downstream is accountable for the result. Record matching is probabilistic rather than exact, so false matches and missed matches both carry meaningful cost. You will not be starting from an empty repository. We operate an established platform for source custody, extraction, and retrieval, and its architect is a member of this team, so existing design decisions are documented and accessible. Your work will focus on new capability rather than maintenance: record matching, calibrated scoring, and grounded generation, hardened for the target environment. We build with current tooling and expect the same, including the use of AI assistance in our own engineering practice. This is a fully remote role with occasional travel (up to 25%) to DEFCON AI HQ, customer sites, and vendor facilities as required. ## Key Responsibilities The technical work falls into four areas. Deep expertise in all four is not expected, so please indicate where your depth lies when you apply. The engineering standards that follow apply to everyone on the team. Data Modeling and Record Matching - Design and maintain the graph of entities, records, and the typed relationships between them - Implement probabilistic matching, including blocking, candidate generation, pairwise scoring, clustering, and threshold policy - Build deduplication and known-record suppression - Establish provenance so that every node and edge traces to the source that asserted it - Produce interface and data-flow design documentation detailed enough to serve as an implementation reference for other engineers Scoring and Calibration - Develop relevance and priority models over large, imperfect record sets - Own calibration and threshold design, establishing what a score means rather than only how it ranks - Design abstention policy that routes uncertain and high-risk cases to a person rather than returning a confident answer - Perform feature engineering, establish baselines before introducing complex models, and conduct error analysis that accounts for the differing cost of false positives and false negatives Retrieval and Generation - Implement embeddings, vector storage, and retrieval across a large provenance-tracked evidence base - Integrate language models through an approved managed service, and maintain a self-hosted or open-weight alternative within the same boundary - Design prompts and output schemas - Bind generated text to cited source records, and treat "insufficient evidence" as a valid system response rather than forcing a conclusion - Own model packaging, serving, versioning, and rollback Pipelines and Source Handling - Build secure ingestion, transformation, validation, and publishing across structured, semi-structured, and unstructured sources - Implement quality checks, schema validation, lineage capture, and audit logging - Establish source drift detection so that degradation is surfaced rather than carried into the analysis - Generate statistically representative synthetic data so that development can proceed ahead of live data access Engineering Standards - Work to the data model and standards set by the Data Lead, who approves designs and owns them through customer review - Document assumptions, caveats, transformation logic, and known limitations, since deliverables are formally reviewed - Instrument telemetry so that measurement does not require manual reconstruction - Maintain the audit trail covering recommendations, human overrides, and model versions - Submit model and pipeline changes through a gated release process rather than deploying in place Required Qualifications - 5+ years of experience in data engineering, data architecture, applied machine learning, ML engineering, or production analytics engineering - Strong Python and SQL, with demonstrated experience working with large, imperfect operational data - Experience delivering systems for sustained operational use rather than exploratory analysis alone - Routine use of AI-assisted development, with informed judgment about where it adds value and where its output requires verification - Ability to explain a technical decision to a stakeholder who must defend that decision without understanding its internals - US Citizenship Required - Active US Secret clearance. The work is performed in a controlled government cloud environment and requires a favorable investigation and CAC eligibility from the start - Elevated personnel security requirements apply to portions of this work and are discussed during screening - Willingness to travel up to 25% to customer sites, DEFCON AI HQ, and vendor facilities as required ## Preferred Qualifications - Clearance: active Top Secret - Matching: direct experience applying probabilistic matching to inconsistent identity data, including names, dates, addresses, and identifiers, and familiarity with the failure modes of each. Record linkage, master data management, or identity management. Graph data modeling. PostgreSQL and pgvector or comparable. Graph algorithms applied in production - Modeling: model calibration and threshold design. Cost-sensitive learning where error types carry unequal consequences. scikit-learn, XGBoost, PyTorch - Retrieval and generation: retrieval-augmented generation in production. Prompt and output-schema design. Establishing that generated output remains grounded in its sources, and testing to confirm it. Self-hosted or open-weight model operation. Fine-tuning, adapters, or custom embeddings - Pipelines: AWS Glue, Airflow, dbt, Spark, Kafka, or NiFi. Unstructured and semi-structured document ingestion. Synthetic or representative test data generation - Environment: federal DevSecOps, RMF, ATO, or DoW cloud environments. Hardened base images. Experience advancing a pipeline from development through accreditation and deployment - Domain: sensitive federal or defense data, and work performed under privacy or comparable handling constraints - Responsible AI: documentation, model cards, fairness testing, and model monitoring. NIST AI RMF or comparable practice What Success Looks Like - A data model that the rest of the team builds on without needing to redesign it - Matching decisions that can be explained and defended to a non-technical reviewer - Models whose miss rate is characterized, not only their overall accuracy - Generated explanations that assert no more than the sources support, with the citation path intact - Pipelines that surface problems early and trace them to a specific source - Consistent development progress, including during periods when live data is not yet available 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: $150,000-$200,000. This represents the typical salary range for this position based on experience, skills, and other factors. We’re an Equal Opportunity Employer: You’ll receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability. Applicant Data Disclosure By submitting an application, you acknowledge that Defcon AI uses third-party service providers to facilitate its recruitment and hiring processes. These providers include applicant tracking systems, candidate verification platforms, and fraud detection tools (collectively, "Hiring Platforms"). Your application materials, including your résumé, cover letter, work samples, responses to application questions, and any other information you submit, may be transmitted to and processed by these Hiring Platforms for the following purposes: - 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. Applications that are flagged through this process as containing indicators of fraud or material misrepresentation may be declined from further consideration. If you have questions about the status of your application or the evaluation process, please contact recruiting@defconai.com. Defcon AI requires its Hiring Platform providers to process your information solely for the purposes described above and in accordance with applicable law. Your information will be retained only for as long as necessary to fulfill these purposes and any applicable legal obligations, after which it will be deleted in accordance with Defcon AI's data retention policies. For more information about how your data is used, please refer to our Privacy Policy and [Applicant Privacy Notice](https://nam09.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.redcellpartners.com%2Fapplicant-privacy-policy%2F&data=05%7C02%7Ckat.creamer%40redcellpartners.com%7Cc0f94f3daed94dc7503108de8b61955e%7Cf861de501a2a42359dbf28afd57d1d97%7C0%7C0%7C639101448841578570%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=WoPiBMZqQyPPK5N4E1sCagkbMY2S8P3aSRSoy7T4los%3D&reserved=0). ## About DEFCON AI ## Company Overview - **One-liner**: DEFCON AI builds AI-powered decision-augmentation platforms that optimize complex operations under uncertainty for national security, manufacturing, logistics, and healthcare organizations. - **Entity Type**: Private (Seed stage; raised $44M total funding) - **Headquarters**: McLean, Virginia, United States - **Founded**: 2022 - **Founders**: Yisroel Brumer (Co-Founder & CEO) and Grant Verstandig (Co-Founder & Executive Chairman) ## Core Business - **Primary industries**: National Security/Defense, Manufacturing, Logistics & Transportation, Healthcare - **Target customers**: B2B — primarily U.S. Department of Defense and other government agencies, as well as large commercial enterprises in manufacturing, logistics, and healthcare. - **Mission or purpose**: To deliver decision-augmentation capabilities that help organizations anticipate disruption, evaluate alternatives in real time, and make confident decisions before disruptions cascade. ## Products & Services - **ARTIV Air**: Cloud-native optimization platform for airlift planners to rapidly generate and evaluate multiple mission scenarios, balancing effectiveness, efficiency, and resiliency for routing mission-critical cargo and personnel. - **R-ALIGN**: Enables logistics planners to model and evaluate global multimodal operations (air, sea, rail, road) using time-sensitive optimization in contested and dynamic environments. - **FlightForge**: AI-driven tool that delivers mission-ready flight schedules in seconds, balancing key factors for accuracy and efficiency with real-time crew-to-sortie visibility. - **DockForge**: Optimizes ship maintenance scheduling by assigning jobs across dry docks and shipyards, maximizing throughput and allowing planners to explore trade-offs. - **R-IMS (Resilient Infrastructure Management System)**: Provides real-time view of capacity, dependencies, and schedule risk through simulation and scenario analysis for infrastructure and program teams. - **HelioNet**: Helps enterprises design resilient, cost-efficient global logistics networks through advanced modeling and long-horizon optimization (warehouse/hub location, tariff/disruption scenarios). - **SimSource**: Advanced optimization, simulation, and forecasting platform for managing complex, nested scheduling demands under uncertainty in manufacturing. - **Synapse Scheduler**: Uses optimization, ML, and LLMs to generate workforce schedules that meet staffing needs and individual preferences (targeting healthcare). ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed. - **Key Metric**: Total funding of **$44.0M** (Seed round led by Bessemer Venture Partners in August 2024; earlier venture round in October 2022). - **Notable Investors/Partners**: Bessemer Venture Partners (lead), Red Cell Partners, and other undisclosed investors. The company was founded in response to a direct request from the U.S. Department of War. - **Growth Signals**: Rapid transition from concept to mission-ready platform since founding in 2022; growing network of partners; expansion into commercial sectors (manufacturing, healthcare, logistics) beyond initial defense focus. LinkedIn shows 3,361 followers (+33.4% yearly). ## Competitive Advantages - **Deep domain expertise**: The team combines senior defense leaders, algorithm developers, and operators, bridging theory and real-world execution. - **Proven government pedigree**: Founded to meet a direct need from the Department of War, giving it strong credibility and an existing customer base in national security. - **Cross-industry applicability**: Core optimization technology is platform-agnostic and has been adapted to manufacturing, healthcare, and logistics — not just defense. - **Focus on uncertainty**: Unlike traditional static planning tools, the entire product suite is built to handle contested, dynamic, and uncertain environments. ## Strategic Focus - **Current priorities**: Scaling the platform across multiple industries (defense, manufacturing, logistics, healthcare) and deepening capabilities in resilient optimization. - **Direction for growth**: Expanding the partner network, continuing to win government contracts, and building out commercial applications for complex scheduling and supply chain resilience. ## Why Work Here - **Culture highlights**: Mission-focused team of world-class AI engineers, data scientists, and mathematics experts working on pressing national challenges. Emphasis on collaboration, transparent communication, and operational impact. - **Remote/hybrid/office policy**: **Remote-first** — ability to work fully remote within the United States. Certain roles may have in-office requirements. - **Notable perks**: 100% employer-paid health insurance (medical, dental, vision) for employee and family; Unlimited PTO with management approval (all federal holidays observed); 14 weeks paid parental leave (maternity and paternity) at normal pay; 401K and FSA available; professional development and continued learning opportunities. - **Engineering culture**: Building with bleeding-edge AI, mathematical optimization, and mission-grade software engineering. The team values rapid iteration and real-world deployment over theoretical work. ## Sources 1. [defconai.com](https://www.defconai.com/) 2. [defconai.com/careers](https://www.defconai.com/careers) 3. [defconai.com/about](https://www.defconai.com/about) 4. [boards.greenhouse.io/defcon](https://boards.greenhouse.io/defcon) 5. [linkedin.com/company/defcon-ai](https://www.linkedin.com/company/defcon-ai) ## Other roles at DEFCON AI - [Technical Director, AI Decision Systems](https://feeny.ai/job/technical-director-ai-decision-systems-defcon-ai-united-states-86dmt45tm7rm) — United States - [VP of Defense Solutions & Growth - Clearance Required](https://feeny.ai/job/vp-of-defense-solutions-growth-clearance-required-defcon-ai-washington-vxknjzce6jqk) — Washington, DC - [Cloud Systems Engineer](https://feeny.ai/job/cloud-systems-engineer-defcon-ai-united-states-aqftgccjd4j4) — United States - [QA Engineer - Clearance Required](https://feeny.ai/job/qa-engineer-clearance-required-defcon-ai-united-states-8ftxc8xawcbs) — United States - [Software Project Lead](https://feeny.ai/job/software-project-lead-defcon-ai-united-states-nx0h45w8ztys) — United States - [Data & ML Engineer](https://feeny.ai/job/data-ml-engineer-red-cell-partners-united-states-6r421mbxjc76) — United States