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AI Engineer, Senior Architect

Columbia, MD

Clarity Innovations is a trusted national security partner, dedicated to safeguarding our nation’s interests and delivering innovative solutions that empower the Intelligence Community (IC) and Department of Defense (DoD) to transform data into actionable intelligence, ensuring mission success in an evolving world.

Our mission-first software and data engineering platform modernizes data operations, utilizing advanced workflows, CI/CD, and secure DevSecOps practices. We focus on challenges in Information Warfare, Cyber Operations, Operational Security, and Data Structuring, enabling end-to-end solutions that drive operational impact.

We are committed to delivering cutting-edge tools and capabilities that address the most complex national security challenges, empowering our partners to stay ahead of emerging threats and ensuring the success of their critical missions. At Clarity, we are people-focused and set on being a destination employer for top talent, offering an environment where innovation thrives, careers grow, and individuals are valued. Join us as we continue to lead innovation and tackle the most pressing challenges in national security.

Seeking an experienced AI platform architect to lead the technical direction and delivery of a baseline product for building and running AI agents in secure government environments. This platform provides a complete, ATO-ready agent development and execution environment, deployable from IL2 through IL6+, that operates seamlessly in both connected (frontier model API access) and disconnected (local model execution) modes.

The ideal candidate will architect and evolve the platform's core infrastructure, including agent orchestration, model access layer, AI ecosystem integration, MLOps pipelines, and enterprise services integration, while leading a small, high-impact product engineering team. This role requires deep hands-on experience with AI platforms, GPU-accelerated inference, and secure government deployment environments.

This person will serve as the platform's technical face to the customer, leading architectural discussions, aligning its capabilities with mission requirements, and ensuring platform advancements integrate cleanly with the company’s broader product ecosystem. They will own the technical roadmap, drive sprint-level execution, and be accountable for the platform's readiness as a deployable, supportable baseline product.

Core Responsibilities

  • Own the technical architecture across platform infrastructure, agent frameworks, model serving, and deployment automation
  • Lead platform stabilization, Helm-based packaging, and CI/CD pipeline development for repeatable deployment to customer Kubernetes clusters
  • Architect and evolve the AI Gateway ecosystem, including RBAC/ABAC access controls, auto-scaling, observability, and agentic workflow orchestration
  • Design and deliver the MLOps pipeline for on-demand model training, fine-tuning, evaluation, and lifecycle management on GPU-accelerated infrastructure
  • Drive connected/disconnected dual-mode architecture, ensuring agents operate seamlessly across frontier APIs (Claude, GPT-4) and local model runtimes (Ollama, vLLM)
  • Manage the platform's ATO posture, model provenance tracking, data residency controls, and security documentation
  • Coordinate with other product teams to ensure platform integration and avoid duplicated effort
  • Mentor engineers and establish engineering standards for the codebase

Technical Requirements

  • Degree in Computer Science, Engineering, or related field
  • Kubernetes-native platform engineering; deep experience deploying, scaling, and operating complex application stacks on Kubernetes (Helm, operators, ArgoCD, GitOps workflows)
  • AI/ML model serving and hosting; hands-on experience with local model runtimes (Ollama, vLLM, TGI) and cloud-backed inference (AWS Bedrock, Azure OpenAI Service), including GPU scheduling, model caching, and multi-model serving
  • Python and systems programming; strong proficiency in Python, experience building frameworks, APIs, and developer tooling
  • Agent and agentic systems; experience designing and building AI agent architectures, tool-use frameworks, and multi-step workflow orchestration
  • MLOps and model lifecycle; experience building training pipelines, experiment tracking, artifact management, and model deployment automation
  • FinOps and observability; experience implementing cost tracking for LLM/GPU consumption, platform monitoring (OpenTelemetry, Grafana, Prometheus), and alerting
  • Security and compliance; understanding of FedRAMP/DoD IL2-IL6 security controls, ATO processes, RBAC/ABAC policy design, and secure software supply chain practices
  • Infrastructure as Code; experience with Terraform, Ansible, or equivalent for automated environment provisioning
  • Cloud and hybrid; experience across AWS, Azure, and on-premises environments, ability to architect for air-gapped and edge deployments
  • GPU computing; understanding of GPU-based architectures (NVIDIA ecosystem, GPU Operator, InfiniBand), containerized model deployment, and compute resource optimization

Leadership & Communication

  • Proven experience leading small engineering teams (3-6 people) in a tech lead or architect capacity
  • Ability to present and defend architectural decisions to both technical teams and non-technical customer leadership
  • Experience in maintaining a strategic technical dialogue with government customers
  • Track record of translating mission requirements into platform capabilities

Additional Requirements

  • Active TS/SCI w/CI Poly
  • Remote position; occasional travel to customer sites (including Fort Meade, MD) and company offices may be required
  • Familiarity with the Cyber Operations domain
  • Familiarity with Cross-Domain Solution (CDS) dataflows, schemas, and operations
  • Familiarity with Scaled Agile Framework (SAFe)

Preferred Qualifications

  • Experience deploying AI platforms in classified (IL5/IL6) or air-gapped environments
  • Experience with a Model Context Protocol (MCP) specification
  • Familiarity with OPA (Open Policy Agent) for policy-as-code access control
  • Experience with Temporal or similar durable workflow orchestration engines
  • Background in DoD cyber operations, intelligence analysis, or mission planning tool development

 

We are an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

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