AI Solution Engineer

Location: Hybrid in Herndon, VA — onsite Tuesday through Thursday; onsite requirements may increase based on business needs
Schedule: 40 hours per week
Employment: Contract, with potential to convert to a full-time role after one year
Openings: 1
Citizenship requirement: Must be a U.S. citizen and hold only U.S. citizenship; dual citizenship is not permitted

Position Overview

We are seeking an AI Solution Engineer who can help business teams identify useful AI opportunities and turn promising ideas into working prototypes. This role combines consultation and hands-on development: you will assess workflows, design solutions using an enterprise AI platform, and build proofs of concept that demonstrate technical feasibility and potential business value.

Responsibilities

• Partner with business teams to understand processes, gather requirements, and identify opportunities to reduce manual effort with AI and automation.
• Translate business needs into practical technical solutions using enterprise AI platform capabilities.
• Develop value assessments that estimate the potential return and effort savings of proposed use cases.
• Guide teams on generative AI approaches and help them adopt available platform capabilities.
• Build functional proofs of concept in a sandbox environment using tools and patterns such as AWS OpenSearch, retrieval-augmented generation (RAG), and large language model orchestration.
• Test business data to assess whether it can support a proposed AI application.
• Maintain a development environment connected to platform APIs and services as new features are released.
• Create reusable code samples and templates to help other developers build on the platform.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.
• Experience developing with Python or JavaScript and working with RESTful APIs.
• Familiarity with cloud-based data services such as AWS OpenSearch and Amazon S3.
• Understanding of generative AI concepts, including language models, prompt engineering, and RAG.
• Ability to break down complex business workflows into clear opportunities for automation.
• Strong communication skills and the ability to explain technical concepts to nontechnical stakeholders.