AI Solutions Engineering & Transformation Manager

Required Academic and Professional Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Statistics, Mathematics, or a related quantitative/technical discipline.
• Preferred: MBA, postgraduate degree or executive education in AI/ML.
• Preferred certifications: Microsoft Azure AI Engineer / Azure Solutions Architect, Google Cloud AI/ML certifications, or recognized GenAI / responsible AI credentials.
• 8–12 years of professional experience in AI solution engineering and transformation, digital transformation, solution architecture, consulting, intelligent automation
• At least 3 years of experience working on AI, analytics, automation, data-driven or digital solution initiatives where technology was used to solve business workflow problems.
• Demonstrated hands-on exposure to building or co-building AI solutions, prototypes, MVPs, automations, AI assistants, analytics tools, workflow applications or data-driven solutions.
• Experience in a GCC or financial services or consulting environment is strongly preferred Competency Area and Required Capabilities
• AI and GenAI fluency - LLMs, GenAI, prompt engineering, RAG, agents, model evaluation, AI risks ​
• Architecture thinking - Data flow, integration, APIs, cloud AI services, security and deployment considerations
• Hands-on development - Python, APIs, automation tools, low-code tools, AI platforms, testing approaches.
• Business consulting - Problem framing, value sizing, stakeholder interviews, prioritization, business cases.
• Delivery leadership - Scope management, dependency tracking, implementation handoff, adoption planning .
• Governance mindset - Privacy, security, responsible AI, risk controls, human-in-loop design .
• Communication - Executive storytelling, workshop facilitation, clear documentation
• Morningstar is an equal opportunity employer.
• Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.