AI Solutions Engineer, Global

Position Overview

AI Solutions Engineer, Global – remote, United States. Hands‑on technical builder within Vantage’s Accelerators team, responsible for transforming validated business requirements into working AI prototypes that demonstrate tangible value within aggressive 6‑week development cycles.

• Design and deliver AI‑powered prototypes within 6‑week sprint cycles, producing production‑quality code that demonstrates business value and supports future enterprise productization.
• Build intelligent solutions leveraging the Microsoft
  365 ecosystem, including Azure AI Services, Azure OpenAI, Copilot Studio, and Power Platform.
• Partner with Accelerators and Navigators to translate validated opportunities into working solutions, providing feedback on feasibility, performance, and implementation complexity.
• Apply SDLC best practices—version control, code reviews, automated testing, and CI/CD—within a rapid prototyping environment to balance quality and speed.
• Produce clear technical documentation (code, APIs, deployment, and architecture decisions) to enable seamless handoff to Development teams.
• Demonstrate prototypes to stakeholders, translating technical capabilities into business value and incorporating feedback into iterative improvements.
• Make pragmatic engineering decisions that balance speed, technical debt, and long‑term scalability.
• Develop solutions using Halo and Copilot platforms in alignment with enterprise architecture and platform standards.

• Develop AI solutions using Python, Type Script/JavaScript, and modern frameworks, including ML models, agentic systems, NLP, and intelligent automation.
• Integrate Azure AI services such as Azure OpenAI, Azure Machine Learning, Cognitive Services, and Document Intelligence into enterprise‑ready solutions.
• Build custom Copilots using Copilot Studio to support conversational AI, workflow automation, and decision support within Microsoft
  365.
• Design data pipelines and ETL processes to prepare enterprise data for AI use, ensuring data quality, privacy, and performance.
• Implement APIs, webhooks, and integrations connecting AI solutions with enterprise platforms (Microsoft
  365, SharePoint, Power Platform, Salesforce, and operational systems).
• Rapidly evaluate and experiment with emerging AI technologies, focusing on solutions suitable for production environments.
• Participate in code reviews, pair programming, and knowledge sharing to ensure prototype quality and team capability growth.
• Embed security, privacy, and governance controls from the outset, meeting enterprise compliance standards.
• Create automated tests and validation checks to verify solution accuracy, reliability, and readiness for demonstrations.
• Troubleshoot and resolve complex technical and integration issues while documenting learnings.
• Package prototypes with deployment scripts, configuration documentation, and user guides for stakeholder demonstrations.
• Support handoff to Development teams through architecture walkthroughs, documentation, and knowledge transfer.
• Stay current on Microsoft AI platform updates and industry best practices, applying relevant innovations to prototyping efforts.
• Handle additional duties as assigned by Management.

• Bachelor’s degree in Computer Science, Software Engineering, or related field; advanced degree or relevant AI/ML certifications preferred.
• Strong hands‑on experience building AI/ML solutions using modern frameworks (e.g., Lang Chain, Semantic Kernel, or similar agentic platforms).
• Proficiency in Python and Type Script/JavaScript, with a track record of writing clean, maintainable, well‑documented code.
• Deep experience with Microsoft Azure, including Azure OpenAI, Azure AI Services, Azure Functions, Logic Apps, and Power Platform.
• Experience developing within the Microsoft Copilot ecosystem (Copilot Studio, Microsoft Graph, Teams, SharePoint).
• Solid understanding of machine learning, NLP, retrieval‑augmented generation, prompt engineering, and agentic system design.
• Experience with modern development practices including Git, CI/CD pipelines, containerization, infrastructure as code, and cloud‑native architectures.
• Strong API and…