Lead DevOps Engineer; AI​/ML Ops Security Clearance

Position: Lead DevOps Engineer (AI/ML Ops) with Security Clearance
Design, scale, and secure mission-critical AI/ML systems.
Prime Solutions Group (PSG), Inc. is seeking a Lead Dev Ops Engineer (AI/ML Ops) to serve as a hybrid senior technical contributor and team leader, responsible for designing, implementing, and operating secure, automated machine learning and data pipelines across cloud and on-premise environments. In this role, you will sit at the intersection of machine learning, data engineering, and Dev Sec Ops , ensuring ML models and data-driven services are scalable, secure, observable, and compliant across their full lifecycle—from data ingestion and feature engineering through training, deployment, monitoring, and retraining.

You will guide technical execution, mentor engineers, and make key architectural and tooling decisions for PSG’s MLOps platforms. Building on PSG’s established Dev Sec Ops  foundation (CI/CD, Infrastructure-as-Code, security baselines), you will extend capabilities to include experiment tracking, model registries, drift detection, and model performance monitoring. This is a fast-paced, high-impact opportunity to deliver enterprise-scale AI/ML solutions while directly supporting U.S. national security missions.

Key Responsibilities
- Lead the design, implementation, and operation of ML-focused CI/CD pipelines supporting data ingestion, feature engineering, model training, evaluation, and deployment across dev, test, staging, and production environments.
- Apply and adapt MLOps best practices within existing Dev Sec Ops  workflows, including:

- Data quality checks and schema validation - Model validation and promotion gates - Model performance and drift monitoring
- Architect and oversee training and inference platforms, including experiment tracking, model registries, and automated retraining pipelines.
- Oversee secure integration of Infrastructure-as-Code, containerization, and orchestration (Docker, Kubernetes) for ML and data workloads, including GPU and high-performance compute resources.
- Mentor and guide engineers in MLOps and Dev Sec Ops  practices, promoting automation, observability, and security-first design.
- Collaborate with cross-functional teams (data science, software engineering, research, IT, cybersecurity, systems engineering) to ensure ML system reliability, performance, and compliance.
- Lead technical risk assessments and contribute to incident response for ML and data systems (e.g., model degradation, data quality issues, pipeline failures).
- Serve in a hybrid role as both:

- A senior hands-on engineer contributing to pipelines, infrastructure, and monitoring - A technical leader guiding small to mid-sized MLOps initiatives
- Make informed technical decisions across ML, data, security, and operations domains, resolving complex multi-disciplinary challenges.
- Evaluate ethical and operational considerations in AI/ML deployment (e.g., bias, data constraints, mission risk) and recommend appropriate mitigations.
- Stay current on emerging MLOps, AI platform, and data engineering technologies, recommending adoption where beneficial. Requirements
- U.S. Citizenship
- Active Top Secret clearance or higher
- Bachelor’s degree in Computer Science, Engineering, Data Science, Applied Mathematics, or related field
- 5–9+ years of experience in one or more of the following:

- MLOps or ML platform engineering - Dev Ops / Dev Sec Ops  / SRE supporting data or ML workloads - Data engineering with production ML integration - Applied machine learning in production environments
- Strong experience with CI/CD tools (Jenkins, Git Lab CI, Git Hub Actions, Circle

CI) and modern Git workflows
- Hands-on experience with Infrastructure-as-Code (Terraform, Ansible, Cloud Formation) and Kubernetes
- Proficiency with ML and data technologies, including:

- Python and ML/data libraries (Num Py, pandas, scikit-learn, PyTorch, Tensor Flow) - Workflow/orchestration tools (Airflow, Kubeflow, Prefect, Dagster) - Experiment tracking and model registries (MLflow, Weights & Biases, Sage Maker)
- Experience integrating security and governance into ML environments (image/dependency scanning, SBOMs, secrets management, IAM)
- Familiarity with NIST, FedRAMP, and…