Early Career IT Solutions Architect - Applied AI Deployment - Hybrid

Sandia Corporation • Albuquerque, NM

55d • $114,000 - $227,500 • Hybrid

About The Position

Sandia's artificial intelligence (AI) team is building the U.S. Department of Energy's (DOE) next-generation AI Platform, an integrated scientific AI capability that delivers rapid, high-impact solutions for national security, science, and applied energy missions. The Platform is based on three pillars: Models, Infrastructure, and Data. As an IT Solutions Architect on Sandia's Applied AI Deployment team, you will translate the AI team's emerging Platform capabilities into robust, scalable enterprise solutions. You'll work across the Models, Infrastructure, and Data pillars to define end-to-end architectures that connect AI systems to enterprise data sources, dashboards, and collaboration tools. In this role, your technical leadership will ensure AI solutions for agile deterrence, autonomous energy operations, and critical-minerals discovery move seamlessly from prototype to production. We anticipate multiple IT Solutions Architect hires that collectively span the set of responsibilities and skills described below. Likewise, new hires will be expected to work in conjunction with existing Sandia staff and teams from other DOE laboratories to deliver on this ambitious, fast-paced project. Importantly, we anticipate that while AI Platform development will leverage existing AI and data science tools extensively, success will also require considerable innovation and problem solving to address the unique needs of DOE applications. If this sounds like an exciting challenge to you, we look forward to reading your application! You will be part of a multi-disciplinary, mission-focused team delivering foundational data capabilities for transformative AI systems in national security, energy, and critical materials. Occasional travel may be required. If you¿re passionate about building the data backbone for next-generation AI at scale, we want to hear from you. The selected applicant can work a combination of onsite and offsite. The selected applicant must live within a reasonable distance for commuting to the assigned work location when necessary.

Requirements

• Bachelor's degree in Computer Science, Data Science, Statistics, or a related STEM field of directly relevant experience, or an equivalent combination of education and experience
• Ability to obtain and maintain a DOE Q clearance
• Demonstrated expertise in building production AI workflows
• Familiarity with integration patterns for hybrid HPC's cloud-edge environments
• Experience with pilot production deployments of large language models, computer vision services, and agentic workflows
• Familiarity with reference designs and secure deployment blueprints that incorporate enclaves, attribute-based access controls, and compliance guardrails
• Experience with building reusable templates and APIs that accelerate adoption by mission teams
• Experience with connecting AI systems to enterprise data sources, dashboards, and collaboration tools
• Familiarity with with MLOps pipelines (e.g., MLflow, Kubeflow, or Vertex AI) for deployment and monitoring.
• Experience with secure deployment of AI tools
• Familiarity with cloud platforms (AWS, Azure, or GCP) and container orchestration (Kubernetes)
• Experience implementing data governance and metadata management tools (e.g., Apache Atlas, DataHub, Collibra)
• Familiarity with data policies for classified, export-controlled, or proprietary data

Nice To Haves

• Graduate degree (M.S. or Ph.D.) with a significant applied AI deployment component
• Ability to work effectively in a dynamic, interdisciplinary environment, guiding technical decisions and mentoring junior staff
• Strong written and verbal communication skills, with the ability to present complex data concepts to diverse audiences
• Ability to obtain and maintain an SCI clearance, which may require a polygraph test.

Responsibilities

• AI Solution Development & Deployment
• Design, prototype, and deploy AI-driven applications that solve real organizational challenges.
• Integrate large language models (LLMs), computer vision, and other AI capabilities into production environments.
• Build and maintain APIs, pipelines, and interfaces that connect AI models to enterprise systems.
• R&D Translation
• Evaluate emerging AI tools, frameworks, and research from academia and industry.
• Rapidly prototype promising technologies to assess feasibility and value.
• Operationalize proven concepts into robust, user-friendly systems.
• Workflow & Automation Engineering
• Build intelligent workflows that automate data processing, analysis, and decision support.
• Leverage orchestration tools and MLOps practices for reliable AI lifecycle management.
• Design systems that integrate human feedback and oversight where needed.
• Collaboration & Enablement
• Partner with data curators to ensure clean, context-rich data fuels AI solutions.
• Collaborate with domain experts to define use cases and success metrics.
• Provide guidance and templates that help other teams safely and effectively adopt AI tools.
• Quality, Ethics, and Governance
• Implement responsible AI principles, including bias testing, explainability, and auditability.
• Document model assumptions, limitations, and operational dependencies.
• Ensure compliance with data protection and organizational security policies.
• Design integration patterns for hybrid HPC's cloud-edge environments
• Pilot production deployments of large language models, computer vision services, and agentic workflows.
• Author reference designs and secure deployment blueprints, incorporating enclaves, attribute-based access controls, and compliance guardrails
• Build reusable templates and APIs that accelerate adoption by mission teams
• Connect AI systems to enterprise data sources, dashboards, and collaboration tools
• Work with MLOps pipelines for deployment and monitoring.
• Collaborate with IT and cybersecurity teams to deploy AI tools securely.
• Create documentation, tutorials, and reusable components to scale adoption.

Benefits

• Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work 4 ten-hour days each week) compressed workweeks, part-time work, and telecommuting (a mix of onsite work and working from home)
• Generous vacation, strong medical and other benefits, competitive 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Industry: National Security and International Affairs
• Number of Employees: 5,001-10,000 employees