SAIC

AI Platform Engineer - SETA

SAIC$200K — $240K *
Education, Government & Non-Profit
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree plus 14+ years, Master's plus 12+ years, PhD or JD plus 9+ years of experience.
  • Experience with AI/ML, data, cloud, or platform engineering in government or enterprise contexts.
  • Familiarity with Microsoft Azure and/or AWS ecosystems.
  • Knowledge of cloud architecture, containers, APIs, and secure systems integration.
  • Understanding of how AI applications interact with platform components like storage and pipelines.
  • Experience creating technical assessments or recommendations for leadership.
  • Strong written and verbal communication skills.
  • Requires TS/SCI clearance with polygraph.

Responsibilities

  • Provide SETA support for AI platform architecture and integration.
  • Advise on AI/ML platform design across various deployment models.
  • Support decisions on Azure, AWS, and data pipelines.
  • Evaluate platform readiness for AI workloads, including security and scalability.
  • Assess vendor offerings and implementation approaches.
  • Develop technical documentation and executive briefs.
  • Coordinate with various stakeholders to align platform efforts with mission outcomes.
  • Identify integration risks and recommend mitigation strategies.
  • Educate stakeholders on AI platform concepts and best practices.

Benefits

  • Work with cutting-edge AI technologies.
  • Engage in mission-focused environments with impactful work.
  • Opportunities for continuous learning and experimentation.
  • Collaborative work with government and technical teams.
  • Access to a robust support network for technical development.
Full Job Description
Job Description

Description

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.

Key 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.
  • ssist 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.

Qualifications
  • Bachelors and fourteen (14) years or more experience; Masters and twelve (12) years or more experience; PhD or JD and nine (9) years or more experience.
  • 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.
  • TS/SCI with polygraph.

Target salary range: $200,001 - $240,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

Overview

SAIC accepts applications on an ongoing basis and there is no deadline.

About SAIC

Science Applications International Corporation (SAIC) is a technology integrator in the technical, engineering, intelligence, and enterprise information technology markets. SAIC has approximately 26,000 employees and operates in more than 70 countries. The company was founded in 1969 and is headquartered in Reston, Virginia. SAIC provides services to the U.S. government, including the Department of Defense, the intelligence community, and civilian agencies. The company also serves commercial customers in the healthcare, energy, and financial services sectors.
Learn more about SAIC
Size
26,000 employees
Market Cap
$6 billion
Industry
Net Income
$206 million
Founded
1969
5 Year Trend
+10.7%
Revenue
$6.8 billion
NASDAQ

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