AI Solutions Engineering & Transformation Manager

The Manager – AI Solutions Engineering & Transformation will help Morningstar’s India GIH teams turn AI use-case ideas into practical designs, prototypes, MVPs and implementations. Acting as an internal advisor, solution architect and hands-on delivery lead, the manager will support business, operations, research, technology and enabling functions, including teams without dedicated AI engineering capacity.

Responsibilities

• Work with functional leaders, managers and AI Champions to identify workflow problems and frame outcome-oriented use cases. Define scope and measures such as hours saved, throughput, accuracy, cycle time, rework and user satisfaction.
• Design solutions covering user and data flows, model and tool selection, integrations, controls, monitoring and operational ownership. Assess options including Microsoft Copilot, Copilot Studio, Azure OpenAI, OpenAI APIs, AWS Bedrock, internal and vendor platforms, OCR/document AI, data pipelines and traditional automation. Collaborate with technology, security, data and architecture teams on feasibility and enterprise alignment.
• Build or co-build prototypes and MVPs, including prompt workflows, lightweight agents, retrieval-enabled assistants, automation flows, simple interfaces, evaluation datasets and testing scripts. Own selected initiatives through discovery, pilot and implementation handoff, managing milestones, dependencies, risks and stakeholder decisions.
• Coach teams on prompt design, experimentation and impact measurement. Produce reusable templates, architecture patterns, RAG checklists, evaluation rubrics and governance guidance. Incorporate human oversight, privacy, security, fairness and quality evaluation; address risks including sensitive-data exposure, hallucinations, regulatory constraints and model drift.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Statistics, Mathematics or a related technical or quantitative discipline. Requires 8–12 years of professional experience in AI solution engineering and transformation, digital transformation, solution architecture, consulting or intelligent automation, including at least 3 years on AI, analytics, automation, data-driven or digital initiatives addressing business workflows. Hands-on experience building or co-building relevant solutions or MVPs is required.
• Requires AI and GenAI fluency, architecture and development skills, business consulting, delivery leadership, governance awareness and clear communication. An MBA or postgraduate AI/ML education, relevant cloud AI or responsible AI certifications, and experience in a GCC, financial services or consulting environment are preferred.

Morningstar describes a hybrid work environment; its model is four in-office days per week in most locations.