Federal AI Solutions Engineer

Empower, Innovate, Impact! At Team A‑TEK, we empower people to drive innovation that impacts mission! A‑TEK operates at the intersection of mission and innovation by applying our deep domain expertise across the federal markets.

A‑TEK provides enhanced capabilities in application development, digital transformation, enterprise IT, and scientific services to modernize, automate, secure, protect, and enhance the operations of our federal clients.

A‑TEK is seeking a highly technical Federal AI Solutions Engineer to design, build, and operationalize mission‑focused, outcome‑driven solutions across AWS and Azure. This role is remote with occasional on‑site presence at our federal client sites; only Continental US applicants will be considered. The ability to obtain and retain a public trust clearance is required.

• Design, build, and deploy agentic AI pilots that demonstrate measurable mission impact using frameworks such as Strands, Lang Chain, Llama Index, Semantic Kernel, CrewAI, or equivalent.
• Orchestrate multi‑LLM solutions with AWS Bedrock, Azure OpenAI, and other orchestration tools.
• Develop end‑to‑end prototypes integrating cloud‑native services, federal or enterprise data sources, APIs, microservices, and enterprise authentication & security controls.
• Implement prompting strategies, tool orchestration, reasoning loops, planning/execution agents, and autonomous workflows.
• Build and maintain internal AWS and Azure environments using infrastructure‑as‑code (Terraform, CDK, Bicep), container services (ECS, EKS, AKS), secure networking, identity, and data pipelines.
• Create reusable accelerators, starter kits, templates, and reference architectures for rapid pilot development.
• Serve as a hands‑on SME for client‑facing teams to resolve complex technical blockers involving cloud migrations, AI/ML integration, and GenAI agent behavior issues.
• Provide architectural guidance and troubleshoot issues across the engineering lifecycle, collaborating closely with Cloud, Cyber, Data Intelligence, and Agile Engineering Centers of Excellence, program managers, solution architects, delivery teams, and capture/proposal teams.
• Produce internal documentation, patterns, and best practices to expand A‑TEK’s technical knowledge base.
• Ensure all pilots and internal platforms adhere to NIST AI RMF, FedRAMP, Zero Trust principles, secure coding, privacy, ethical AI, and accessibility guidelines.
• Implement logging and monitoring for auditability and responsible AI operations.

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field.
• 3–5 years of hands‑on software development experience (Python preferred; Node.js/Java acceptable).
• Experience building applications on AWS and/or Azure.
• Associate level or higher Solutions Architect certification in AWS or Azure.
• Strong understanding of LLM APIs and ecosystems (e.g., OpenAI, Anthropic, AWS Bedrock, Azure OpenAI).
• Experience with vector databases (e.g., Pinecone, Weaviate, Milvus, FAISS).
• Ability to design and debug distributed cloud systems and AI‑enabled applications.
• Strong communication skills: able to explain complex topics to delivery teams, leadership, and partners.

• Familiarity with containers, serverless, event‑driven architecture.
• Experience working in or supporting secure federal environments.
• Exposure to MLOps, Dev Sec Ops , or continuous ATO practices.
• Prior experience building reusable internal platforms or accelerators.

Salary Range: $135,000 – $150,000 annually (commensurate with experience).

• Benefits:
  Health, dental, and vision insurance; 401(k) with employer match; paid time off; professional development opportunities.

A‑TEK, Inc. is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or status as a qualified individual with a disability, or Vietnam era or other protected Veteran status. Verification of education may be requested before or during the hiring process.