Job Description Summary

The Staff AI Solution Architect will lead the design, development, and deployment of AI-driven enterprise applications supporting data analytics across global functions like Finance and Sourcing. This role involves full lifecycle ownership of AI components using technologies such as Databricks and AWS, ensuring scalable and standardized solutions. Key responsibilities include strategic planning, architecture design, compliance with GDPR/SOX, and integration of Responsible AI practices. The architect will collaborate across teams to shape product roadmaps, drive AI adoption, and deliver measurable outcomes aligned with business goals. Strong technical expertise, leadership, and a data-driven mindset are essential for success in this role.

Job Description

The Staff AI Solution Architect will be responsible for leading the design, development, and support of AI-driven enterprise applications and services that enable data analytics across global functions—including Finance, Treasury, Sourcing, and Enabling Functions. This role entails end-to-end ownership of AI components, encompassing architecture, testing, documentation, and deployment within large-scale data analytics programs. The architect will leverage technologies such as Databricks, Microsoft data fabric, Microsoft AI Foundary and AWS to build scalable, standardized AI solutions that deliver measurable value through the Safety, Quality, Delivery, and Cost (SQDC) framework, with a strong emphasis on the impact of AI initiatives on business.

Key Responsibilities

• Strategic Collaboration: Engage in technical and business discussions to shape the future of AI solution architecture.
• Architecture Planning: Analyze current and future states to develop implementation roadmaps for AI solutions.
• Requirements Gathering: Translate business needs into architectural requirements and contribute to infrastructure governance.
• Solution Development: Partner with service providers to build AI solutions aligned with project goals and enterprise standards.
• Compliance & Standardization: Ensure AI solutions adhere to architectural frameworks and comply with GDPR, SOX, and Responsible AI guidelines.
• Technology Adoption: Research emerging AI technologies and trends to enhance solution design, and explore new capabilities in Databricks and Microsoft.
• Performance & Security Oversight: Monitor deployed solutions to ensure optimal performance and security compliance.

Additional Responsibilities

• Solution Ownership: Collaborate with cross-functional teams, including Data Architecture and Analytics, to define and execute AI solution roadmaps aligned with business strategy.
• Product Roadmap Input: Work with product managers and data architects to shape analytics product roadmaps.
• Technical Integration: Partner with data scientists, engineers, and designers to ensure robust, scalable AI implementations.
• Enterprise Coordination: Support AI initiatives across Vernova HQ to drive innovation and operational excellence.
• Data-Driven Insights: Define and track KPIs to measure the success and impact of AI solutions.
• Post-Launch Optimization: Gather feedback, monitor performance, and iterate on features to enhance value delivery.

Desired Qualifications & Characteristics

• Proven experience designing and deploying cloud-based AI solutions.
• Strong understanding of aligning AI architecture with business objectives.
• Familiarity with automation, DevOps practices, and cloud-native AI tools.
• Ability to adapt AI applications to cloud platforms of Microsoft primary and AWS.
• Expertise on Databricks services and Microsoft AI solution ecosystem.
• Excellent collaboration and communication skills, including stakeholder engagement at all levels.
• Proactive in identifying risks, resolving issues, and driving continuous improvement.
• Open to new ideas and innovative approaches to problem-solving.

Education & Experience

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
• Experience with GE or GE Vernova is highly preferred.
• Demonstrated leadership in managing cross-functional teams and complex projects.
• Strong business acumen with the ability to align technical solutions with strategic goals.
• Excellent analytical, problem-solving, and decision-making skills.
• Experience in building and scaling AI applications in enterprise environments.

Additional Information