Responsibilities

Technical Leadership & Architecture: Lead the design, prototyping, development, and operationalization of enterprise-wide AI/ML capabilities, with a particular focus on advanced generative AI and agentic artificial intelligence systems.
Lifecycle Management (MLOps): Establish and maintain a secure, scalable, and standardized AI/ML Operations environment that handles the entire lifecycle from data curation and preparation through automated deployment and continuous model retraining.
Compliance & Model Governance: Ensure all AI/ML models, training pipelines, and algorithms strictly meet the accreditation criteria mandated by the DIA Quality Assurance Framework (QAF) and relevant ethical AI directives (e.g., Memo U-23-0491/DI).
Assurance & Validation: Lead model validation, adversarial robustness testing, explainability evaluations, and bias detection analysis to safeguard the integrity of intelligence capabilities.
Cross-Functional Collaboration: Serve as the primary technical interface between data scientists, software engineers, DevSecOps teams, and mission analysts to translate complex technical architectures into analytic tradecraft solutions.
Innovation & Research: Stay at the forefront of emerging AI breakthroughs (such as transformer architectures and complex reasoning agents) and formulate proactive recommendations to address complex national security challenges.

Basic qualifications

Clearance: Must possess an active federal TS/SCI clearance.
Education: An advanced degree (Master’s or PhD preferred) in Computer Science, Data Science, Mathematics, or a highly related technical field.
Experience: Demonstrated senior-level experience leading end-to-end AI/ML implementation projects and engineering robust, secure AI operations (MLOps) infrastructure in federal or secure environments.

Years of Experience: 13+ years of specialized experience designing, developing, and embedding advanced neural networks or predictive statistical modeling into production software.
Technical Domain Expertise: Proven experience with state-of-the-art transformer architectures, large language models (LLMs), reinforcement learning, and building complex agentic systems.
DIA Framework Knowledge: Deep familiarity with DIA QAF compliance, model security verification, and the transition of pipelines into cloud-native Platform as a Service (PaaS) or containerized architectures (Kubernetes/OpenShift).
Security & Adversarial Defence: Demonstrated experience implementing zero-trust concepts within data architectures and engineering defenses against model poisoning, membership inference, data exfiltration, or adversarial manipulation.
Thought Leadership: Published peer-reviewed research or widely recognized technical contributions to the broader defense/intelligence AI/ML community.
Real opportunity for career growth in an environment where your achievements will be celebrated
Constant collaboration with numerous teams to ensure client success
A team that respects and embraces your ideas and expertise
Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain
A workplace dedicated to supporting and bettering public safety and government agencies

Very competitive salary based on qualifications and experience
Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
401(k) with company match
Travel & performance incentives
3 weeks paid time off (plus Federal Holidays)
$5K annual training allowance

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Fulltime Ai Ai Engineer Machine Learning