Senior AI Solutions Architect

Description

We are seeking a high-impact AI Solutions Architect to design, deploy, and scale AI/ML solutions that advance federal mission outcomes. This role blends deep technical design, applied engineering, and strategic consulting to deliver secure, ethical, and mission-aligned AI systems.

Candidates will be expected to demonstrate their expertise through real-world examples of work, not just theoretical answers.

Applicants must include the following with their application:

• Public Work Samples: Links to code repositories
  , shipped projects
  , or technical blog posts that showcase relevant technical or architectural work.
• Certification Verification: For any listed certification (e.g., AWS, Azure, GCP, or AI/ML specialization), include a link or credential for verification.
• “How I Used X”
  
  Summary:
  
  For each required technical skill
  , include 1–2 sentences describing how and where you applied it in a real project.
• Example: “Used Lang Chain and RAG to enable LLM-powered search across 50k unstructured PDF documents, reducing analyst retrieval time by 40%.”

At Net Centrics
, we proudly hold a distinguished position as a leader in cybersecurity, cloud, digital transformation, and mission support. With an esteemed clientele that includes the DoD, DHS, Federal Civilian Agencies, and the Intelligence Community, our impact on national security is undeniable. We are a diverse group of intellectually curious people, solving hard problems, and living by our core values while bonded by the shared vision to secure our nation - join us!

• Lead Strategic Discovery: Partner with federal stakeholders to identify high-value AI opportunities, define use cases, and align on mission objectives.
• Design AI-Native Solutions: Architect end-to-end AI/ML systems, including LLMs
  , Retrieval-Augmented Generation (RAG) pipelines, data architectures, and orchestration workflows.
• Technical Design & AI Reasoning: Demonstrate deep understanding of LLM reasoning
  , prompt design
  , model evaluation
  , and implementation trade-offs (e.g., latency vs. accuracy, safety, or data sensitivity).
• Ensure Security & Governance: Integrate solutions meeting NIST SP 1270, DoD Responsible AI Strategy, DoD Responsible AI Toolkit, and NIST SP 800-53 Risk Management Framework
• Accelerate Delivery: Collaborate with Forward Deployed Software Engineers (FDSEs) and development teams to rapidly prototype, test, and iterate solutions.
• Build & Validate Proofs of Concept: Develop Python/Flask-based prototypes
  , microservices, or interactive demos to validate architecture and demonstrate measurable mission value.
• Guardrails & Moderation: Design and implement content filtering
  , moderation
  , and guardrail enforcement for GenAI workflows using techniques such as policy tuning, API filtering, or embedding-based screening.
• Codify and Scale Best Practices: Create reusable frameworks
  , reference architectures
  , and deployment patterns to scale AI across programs and agencies.
• Drive Executive Alignment: Translate technical solutions into clear, outcome-driven narratives for senior government leaders.
• Enable Organizational Scale: Develop training, documentation, and implementation guides to ensure sustainable adoption and knowledge transfer.

• Active DoD Secret Clearance (or ability to obtain one).
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science
  , or related technical field (preferred).
• 7+ years in technical consulting, solution architecture, or field engineering, with an emphasis on AI/ML systems.
• Proven record delivering AI/ML or data-driven solutions for federal or public-sector clients
  .
• Experience managing projects from discovery to production deployment
  .
• U.S. Citizenship required.
• Technical Expertise

Candidates must demonstrate experience and provide “how I used X” context for the following areas:

• AI/ML & LLM Systems: Experience designing and deploying LLM-based systems
  , RAG
  , Lang Chain
  , Semantic Kernel
  , or embedding-based retrieval
  . Understanding of prompt engineering
  , model reasoning, and trade-offs in accuracy, safety, or performance
  .
• Cl…