RemotePosted 12/5/2025Lead/Manager
    Full-time
    Technology
    Platform Architecture
    DevSecOps
    CI/CD
    AI/ML
    Kubernetes

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    Job Description

    Your essential job functions will include but may not be limited to: Own the end-to-end architecture of the Development Platform, including SDLC workflows, CI/CD, source control, artifact management, observability, and associated tooling. Define and maintain SDLC and DevSecOps architecture patterns, reference designs, and guardrails for application, AI/ML, data, and M&S workloads. Architect and drive implementation of compliance-by-design capabilities (policy-as-code, compliance-as-code, automated evidence generation) so that developers operate within guardrails without manual effort. Lead the technical integration and governance of AI coding augmentation tools (e.g., AI-assisted code completion, review, and refactoring) to safely accelerate development while protecting sensitive data and meeting all compliance requirements. Define platform capabilities that specifically enable AI/ML and M&S workflows (e.g., data pipelines, model training/serving, simulation workflows) within the same secure SDLC and CI/CD patterns. Establish architectural patterns for multi-environment, multi-level security use of the Development Platform, including secure promotion paths from unclassified to classified environments. Provide architectural guidance for standardized CI/CD pipelines, reusable templates, and shared components used across engineering teams using various tech stacks. Partner with Cybersecurity SMEs to ensure security and compliance frameworks (NIST, RMF, CMMC, SSDF, etc.) are accurately reflected in platform design and technical controls. Collaborate closely with DevSecOps engineers, software teams, data/AI engineers, and cloud engineers to ensure architecture is implemented correctly, maintainable, and scalable. Define and document platform roadmaps, technical standards, integration patterns, and interface contracts. Mentor engineers on platform architecture, secure SDLC, DevSecOps best practices, and effective use of AI-assisted development within established guardrails. Coordinate with vendors and internal stakeholders to evaluate tools, plan upgrades, manage technical risk, and ensure the Development Platform remains modern, secure, and sustainable. Oversee platform reliability, performance, and scalability at the architectural level, ensuring the Development Platform can support growing AI/ML, M&S, and software workloads. 14+ years of progressive experience in software engineering, DevOps/DevSecOps, or platform engineering, including significant architecture and/or technical leadership responsibility. Demonstrated experience architecting and operating enterprise Development Platforms or software delivery platforms that integrate CI/CD, source control, artifact repositories, and observability tooling. Strong expertise in DevSecOps and secure SDLC practices, including automated testing, security scanning, and policy-as-code/compliance-as-code approaches. Hands-on experience with modern DevOps/DevSecOps toolchains, with substantial professional experience using GitLab as an absolute requirement. Deep experience working with Azure Cloud Services (absolutely required), including networking, IAM, storage, AI, and compute services. Strong background in Kubernetes and container orchestration, including cluster architecture, multi-tenant design, security controls, and GitOps-based deployment models (e.g., Helm, Kustomize, Argo CD). Proficiency with Infrastructure as Code tools (e.g., Terraform, Ansible, Packer, Puppet, or Chef) and configuration management patterns for repeatable platform provisioning and management. Demonstrated ability to interpret and apply security and compliance frameworks (NIST 800-53, RMF, CMMC, SSDF, etc.) to platform design and technical controls. Familiarity with SDLC and platform requirements for AI/ML and/or M&S workloads (e.g., data pipelines, model lifecycle, simulation workflows) in secure environments. Experience evaluating and/or integrating AI-assisted development tools, with an understanding of associated security, compliance, and governance considerations. Solid understanding of networking, identity and access management, TLS, secrets management, and zero-trust principles as they apply to enterprise development platforms. Proficiency in at least one relevant programming (e.g., Python, C#, Go, or similar) to support automation and integration efforts. Proven experience leading technical decision-making, producing architectural documentation, and presenting platform solutions to both technical and non-technical audiences. Bachelor's degree in Computer Science, Computer Engineering, Cybersecurity, or Information Systems; a Master's degree is preferred but not required. US Citizenship required. Ability to obtain and maintain a DoD security clearance; an active clearance is strongly preferred.

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