CRISIL
Website:
crisil.com
Job details:
Role Purpose
Lead the enterprise AI product portfolio and technical governance framework, ensuring AI initiatives are strategically aligned, architecturally sound, responsibly governed, and delivering measurable business value at scale.
This role owns the “what and why” of AI across the organization — translating strategy into prioritized AI products and ensuring industrialized deployment across business units.
Key Responsibilities
AI Product Strategy & Portfolio Ownership
- Define and own the multi-year enterprise AI roadmap aligned to business strategy.
- Evaluate and prioritize AI use cases based on value, risk, feasibility, and data readiness.
- Establish business cases and measurable success metrics for all AI initiatives.
Technical Oversight & Standards
- Set enterprise AI engineering standards including MLOps, model lifecycle management, and observability.
- Ensure alignment with enterprise data architecture, metadata, and governance frameworks.
- Approve AI solution designs before build-to-scale.
- Partner with Enterprise Architecture and Cloud teams to ensure scalability and resilience.
Industrialization & Scale
- Drive transition from experimentation → pilot → enterprise production.
- Promote reusability of models, pipelines, and feature assets.
- Establish AI asset repositories and lifecycle discipline.
Executive Engagement
- Present AI portfolio performance, risks, and realized value to leadership forums.
- Act as strategic advisor to business heads on AI opportunities and constraints.
Responsible AI & Governance
- Institutionalize model governance covering explainability, bias, transparency, and compliance.
- Maintain enterprise model inventory and traceability.
- Collaborate with Risk and Compliance for regulatory readiness.
Ideal Candidate Profile
- 12–18+ years in Data, AI, Product, or Technology leadership roles.
- Proven experience scaling AI solutions in enterprise environments.
- Strong understanding of:
- AI/ML lifecycle and LLM-based solutions
- MLOps and model monitoring frameworks
- Enterprise data architecture and governance
- Cloud AI platforms (AWS/Azure/GCP)
- Experience in regulated industries preferred (Insurance, BFSI, Ratings, Healthcare).
What Success Looks Like
- AI initiatives consistently move beyond POC into scalable production.
- Clear ROI tracking and measurable business impact.
- Strong AI governance with no regulatory surprises.
- Reduced duplication and improved reuse of AI assets.
- Enterprise-wide confidence in AI adoption.
Leadership Attributes
- Strategic product thinker with technical depth
- Influences at CXO level
- Balances innovation with risk discipline
- Drives clarity in complex, cross-functional environments
Why This Role Matters
This role sits at the center of the organization’s AI transformation journey — ensuring AI is not fragmented experimentation but a disciplined, scalable enterprise capability.
Click on Apply to know more.