AI Platform Engineer – Senior

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    "city": "Columbia",
    "region": "MD",
    "country": "United States",
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{
  "lists": [
    {
      "text": "Responsibilities",
      "content": "<div>\n\n<li>Provide SETA support to government leadership and technical teams on AI platform architecture, integration, and sustainment.</li>\n<li>Advise on the design and evaluation of AI/ML platform environments across cloud, hybrid, and enterprise deployments.</li>\n<li>Support platform decisions involving&nbsp;Azure, AWS, Microsoft enterprise services, containerized environments, data pipelines, model hosting, and secure access patterns.</li>\n<li>Assess platform readiness for AI workloads, including compute, storage, networking, identity, security, observability, and scalability considerations.</li>\n<li>Help evaluate vendor offerings, reference architectures, technical tradeoffs,</li>\n<li>and implementation approaches.</li>\n<li>Support the development of technical documentation, architecture artifacts, white papers, decision briefings, and executive summaries.</li>\n<li>Coordinate with program managers, engineers, mission stakeholders, cybersecurity teams, and external partners to keep platform efforts aligned with mission outcomes.</li>\n<li>Identify integration risks, technical gaps, and dependencies, and recommend</li>\n<li>practical mitigation strategies.</li>\n<li>Assist with transition planning from prototype or pilot efforts into sustainable operational capability.</li>\n<li>Educate stakeholders on AI platform concepts, emerging patterns, and implementation best practices in government environments.</li>\n\n</div>"
    },
    {
      "text": "Minimum Qualifications",
      "content": "<div>\n\n<li>Min 12 years with Bachelors, 10 years with Masters degree in Computer Science, Engineering, Information Systems, or related field.</li>\n<li>Experience supporting AI/ML, data, cloud, or platform engineering efforts in government, defense, or enterprise environments.</li>\n<li>Demonstrated familiarity with&nbsp;Microsoft and/or AWS platform ecosystems.</li>\n<li>Working knowledge of cloud architecture, containers, APIs, data services, identity/access management, and secure system integration.</li>\n<li>Ability to understand how AI applications depend on underlying platform components such as model hosting, pipelines, storage, orchestration, and monitoring.</li>\n<li>Ability to understand how AI applications depend on underlying platform components such as model hosting, pipelines, storage, orchestration, and monitoring.</li>\n<li>Strong written and verbal communication skills.</li>\n<li>Naturally curious and energized by learning new technologies.</li>\n<li>Builds, tests, and explores tools independently.</li>\n<li>Passionate about AI and platform modernization.</li>\n<li>Comfortable operating in ambiguous environments and helping teams find a path forward.</li>\n<li>Able to translate complex technical issues into actionable guidance for mixed technical and non-technical audiences.</li>\n<li>Mission-oriented, collaborative, and proactive.</li>\n\n</div>"
    },
    {
      "text": "Preferred Qualifications",
      "content": "<div>\n\n<li>Experience with&nbsp;Azure AI services, AWS AI/ML services, Kubernetes, Docker, MLOps, DevSecOps, Infrastructure as Code, or platform observability tools.</li>\n<li>Familiarity with secure government cloud environments and cross-domain or restricted operational architectures.</li>\n<li>Understanding of AI governance, responsible AI, model lifecycle support, and platform security considerations.</li>\n<li>Experience supporting DoD, IC, or cyber mission organizations.</li>\n<li>Relevant certifications in cloud, systems engineering, cybersecurity, or platform operations.</li>\n\n</div>"
    }
  ],
  "country": "US",
  "createdAt": 1780457200745,
  "updatedAt": null,
  "categories": {
    "team": "0007-0028",
    "location": "Columbia, MD",
    "commitment": "Full-time",
    "department": "Systems Engineer",
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      "Columbia, MD"
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