AI Solution Engineer (26-00279) -

Position

AI Solution Engineer

Duration

2088 Hours

Location

Corporate / Hybrid – Herndon, VA

Description

Possible Conver to hire after 1 year

*Hybrid

Candidate Required to be on site in Herndon Tue-Thurs (May increase based on business needs)

Job Title

AI Solution Engineer

Organization

Central AI & Data Observability (AIDO)

Team

AI Platform Strategy & Services

Location

Corporate / Hybrid – Herndon, VA

Role Overview

As an AI Solution Engineer, you will sit at the intersection of business strategy and hands-on engineering. You will be a key member of the AI & Data Observability team, responsible for helping our Lines of Business (LOBs) transition to "AI-enabled."

This is a "dual-hat" role

you will act as a strategic consultant to identify high-impact AI opportunities and as a technical developer to build Proof of Concepts (POCs) on our enterprise AI Platform. You will help teams reduce Level of Effort (LOE) and improve work products while ensuring all solutions are built with world-class observability and data integrity.

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Key Responsibilities

• Technical Consultancy (The "Strategy" Hat)
• Discovery & Assessment: Partner with LOBs to map existing business processes, capture requirements, and identify friction points where AI/Automation can significantly reduce manual effort.
• Solution Design: Translate vague business requirements into concrete technical solutions that leverage the Hub-and-Spoke AIDO Platform.
• Value Engineering: Develop "AI Value Scorecards" to estimate potential ROI and LOE reduction for proposed use cases.
• Center of Excellence: Assist LOBs with the application of AI use cases with existing and planned AIDO Platform capability. Drive adoption of Generative AI principles and techniques.
• Rapid Prototyping & Development (The "Builder" Hat)
• Platform Mastery: Maintain a current development environment against the AI Platform's APIs and UI services to stay ahead of new feature releases.
• Informal POCs: Conduct rapid technical validation by building functional prototypes in a sandbox environment (utilizing AWS OpenSearch, RAG patterns, and LLM orchestration).
• Technical Feasibility: Perform "smoke tests" on LOB data to ensure it is viable for the proposed AI application before full-scale development begins.
• Reference Implementation: Build and maintain a library of "Golden Path" code samples and templates to accelerate LOB developers.

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Required Qualifications

• Education: Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
• Technical Proficiency: * Experience with Python or JavaScript and interacting with RESTful APIs.
• Familiarity with cloud-based data environments (e.g., AWS OpenSearch, S3).
• Understanding of Generative AI concepts (Language Models, Prompt Engineering, RAG, Other data techniques to support AI).
• Analytical Mindset: Ability to deconstruct complex business workflows into logical steps for automation.
• Communication: Strong ability to explain technical AI concepts to non-technical stakeholders in a persuasive, consultative manner.