AI Platform Engineer

SilverEdge•Columbia, MD

About The Position

SilverEdge is a premier provider of innovative cyber, software, and intelligence solutions, addressing mission-critical challenges for the Department of Defense (DoD), Intelligence Community (IC), and beyond. We are dedicated to delivering impactful results to meet mission goals through cutting-edge technology and expertise. We are seeking an AI Platform Engineer to join our dynamic team. This individual will play a pivotal role in developing innovative and effective solutions for our DoD customers within the IC sector. We are seeking an AI Platform Engineer to advise and support the design, integration, and maturation of AI-enabling infrastructure across mission-focused environments. This role is ideal for a technically strong engineer who understands how to stand up, assess, and guide modern AI platforms in secure government settings, with particular familiarity in cloud and enterprise ecosystems such as Microsoft Azure and Amazon Web Services (AWS). The ideal candidate is not just technically capable, but deeply curious, self-motivated, and passionate about AI. We are looking for someone who continuously learns, experiments, and stays current with emerging tools, architectures, and best practices—even outside formal work requirements. This person should bring both engineering judgment and an enthusiasm for helping government teams adopt AI platforms in a practical, secure, and mission-aligned way.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
Experience supporting AI/ML, data, cloud, or platform engineering efforts in government, defense, or enterprise environments.
Demonstrated familiarity with Microsoft and/or AWS platform ecosystems.
Working knowledge of cloud architecture, containers, APIs, data services, identity/access management, and secure system integration.
Ability to understand how AI applications depend on underlying platform components such as model hosting, pipelines, storage, orchestration, and monitoring.
Experience producing technical assessments, recommendations, or engineering support artifacts for leadership or program offices.
Strong written and verbal communication skills.
Active TS with poly required

Nice To Haves

Experience with Azure AI services, AWS AI/ML services, Kubernetes, Docker, MLOps, DevSecOps, Infrastructure as Code, or platform observability tools.
Familiarity with secure government cloud environments and cross-domain or restricted operational architectures.
Understanding of AI governance, responsible AI, model lifecycle support, and platform security considerations.
Experience supporting DoD, IC, or cyber mission organizations.
Relevant certifications in cloud, systems engineering, cybersecurity, or platform operations.

Responsibilities

Provide SETA support to government leadership and technical teams on AI platform architecture, integration, and sustainment.
Advise on the design and evaluation of AI/ML platform environments across cloud, hybrid, and enterprise deployments.
Support platform decisions involving Azure, AWS, Microsoft enterprise services, containerized environments, data pipelines, model hosting, and secure access patterns.
Assess platform readiness for AI workloads, including compute, storage, networking, identity, security, observability, and scalability considerations.
Help evaluate vendor offerings, reference architectures, technical tradeoffs, and implementation approaches.
Support the development of technical documentation, architecture artifacts, white papers, decision briefings, and executive summaries.
Coordinate with program managers, engineers, mission stakeholders, cybersecurity teams, and external partners to keep platform efforts aligned with mission outcomes.
Identify integration risks, technical gaps, and dependencies, and recommend practical mitigation strategies.
Assist with transition planning from prototype or pilot efforts into sustainable operational capability.
Educate stakeholders on AI platform concepts, emerging patterns, and implementation best practices in government environments.