AI​/ML Integration Tech Lead - Top Secret Clearance

Metric5

The AI/ML Integration Tech Lead bridges long-term strategy, technical execution, and cross-organizational governance to scale AI capabilities across petabyte-scale cyber defense data pipelines. The role drives the evolution of the Defensive Cyberspace Operations (DCO) platform, establishing robust agentic frameworks, rigorous harness evaluations, and secure lifecycle governance across operational mission systems. Beyond primary program delivery, position will also provide support to corporate AI initiatives, applying technical expertise to support 1-2 corporate initiatives per year.

• Long-Term Vision: Define the multi-year AI/ML technical roadmap to transition petabyte-scale cyber data (logs, network telemetry, threat intelligence) from passive monitoring to real-time predictive defense.
• Architecture Oversight: Architect scalable, low-latency machine learning pipelines (real-time streaming and batch) capable of handling massive telemetry throughput for threat detection, anomaly scoring, and automated incident response.
• Prototyping & Innovation: Rapidly prototype novel AI/ML concepts, custom models, and agentic workflows to validate emerging defense capabilities before operational scaling.
• Agentic Architecture & Harness Assessment: Maintain deep technical mastery of emerging agentic workflows, multi-agent patterns, orchestration mechanisms, memory boundaries, and tool‑use execution harnesses. Assess commercial and open‑source agentic solutions for operational viability, architectural feasibility, systemic risk, and scalability within Defensive Cyberspace Operations (DCO) mission workflows, ensuring deterministic controls and human‑in‑the‑loop oversight are preserved.

• Market Evaluation: Conduct technical assessments of 3rd‑party vendor products, evaluation of model performance (precision/recall on cyber data), and bench‑testing in sandbox environments.
• Integration Engineering: Design standard integration hooks, APIs, and data ingestion paths to safely dock vendor applications directly into the core big data infrastructure.
• DCO Platform Integration & Agentic Evaluation: Define architectural, interface, telemetry, identity, and access‑control requirements for integrating AI/ML and agentic capabilities into the DCO Platform, Big Data Platform, and SOC/SIEM/SOAR pipelines. Establish rigorous evaluation criteria and test harness standards to benchmark model groundedness, tool‑use reliability, latency, resource consumption, fail‑safe isolation, and verifiable audit logging.
• Product Testing: Establish rigorous testing protocols to validate vendor claims regarding accuracy, resource consumption, and false‑positive rates under actual operational data loads.

• ATO Process Management: Lead technical documentation, security controls implementation, and threat modeling required to navigate the Authority to Operate (ATO) process for new AI models and software.
• Data & Model Security: Enforce secure AI practices across data pipelines, including data anonymization, model robustness testing (protection against adversarial manipulation), and access controls.
• AI/Agent Security & Lifecycle Governance: Establish system security, compliance, and risk‑mitigation requirements for AI models, prompts, retrieval stores, orchestration logic, and external tool integrations. Define defenses against prompt injection, retrieval poisoning, data tampering, configuration drift, and model supply‑chain vulnerabilities, while governing configuration management, auditing, and retirement standards consistent with DoD AI Ethics and RMF protocols.
• Pipeline Integration: Partner with security…