AI Platform Engineer - SETA

SAIC•Hanover, NH

4d•Onsite

About The Position

Varen, an SAIC Company is seeking an AI Platform Engineer - SETA to join our team. This position is located in Columbia, MD and requires a TS/SCI with polygraph. We are seeking an AI Product Manager - SETA to Contractor SETA 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

TS/SCI with polygraph clearance
Technical expertise in standing up, assessing, and guiding modern AI platforms
Familiarity with cloud and enterprise ecosystems such as Microsoft Azure and Amazon Web Services (AWS)
Engineering judgment
Ability to help government teams adopt AI platforms practically, securely, and in a mission-aligned way

Nice To Haves

Deep curiosity
Self-motivation
Passion for AI
Continuous learning and experimentation
Staying current with emerging tools, architectures, and best practices

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.