AI Solutions Engineer

Since 2004, Vadum has built a brand known for practical innovation that delivers solutions to customers in the competitive field of national defense research and development.


We are seeking a talented and innovative AI Solutions Engineer to join our dynamic team. In this role, you will be responsible for designing, building, and deploying general AI solutions. The ideal candidate will be a generalist and have broad experience in Large Language Models (LLMs), agentic AI, and computer vision. This role sits at the intersection of engineering, product, and customer success, ideal for someone who can solve complex technical problems while working directly with customers to deliver high-impact pilot programs and integrations.


The AI Solutions Engineer will own technical delivery from solution design through deployment, helping customers adopt next-generation AI capabilities while shaping best practices and product evolution. If you are passionate about artificial intelligence and enjoy solving complex technical challenges, we invite you to become a part of our forward-thinking organization.


Key Responsibilities


Solutions Design & Development

  • Architect and build LLM-enabled workflows, generative-AI pipelines, and custom integrations.
  • Architect and build computer vision feature extraction, classification, and object detection pipelines.
  • Develop prototypes, proof of concept, and small-scale pilot systems aligned with customer use cases.
  • Collaborate with product and research teams to translate requirements into scalable, production-ready solutions.

Customer Integration & Deployment

  • Lead technical discovery, solution scoping, and integration planning with customer engineering teams.
  • Deploy AI pilots into customer environments (cloud, on-prem, hybrid).
  • Build and support data ingestion pipelines, API integrations, agent frameworks, and evaluation systems.
  • Troubleshoot technical issues and guide customers through adoption and operationalization.

Technical Support & Enablement

  • Provide hands-on technical guidance to customers during pilot and post-deployment phases.
  • Develop documentation, reference architectures, and repeatable implementation patterns.
  • Train customer teams on best practices for general AI systems and workflow integration.
  • Serve as the technical advocate for customers internally and influence future product direction.

Cross-Functional Collaboration

  • Work closely with engineering to relay customer feedback, edge cases, and new integration requirements.
  • Partner with sales and customer success to support pre-sales demos, solutioning, and scoping discussions.
  • Contribute to internal and external technical materials (whitepapers, demos, templates).

See also

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