Role Summary
- The Vice President – Enterprise AI & Advanced Technologies is a senior leadership role at the forefront of EXL's transformation into an AI-native enterprise. This role will shape how AI is embedded across core operations, decision-making, and enterprise workflows at scale.
- As a key driver of EXL's Client Zero vision, the role offers a unique opportunity to build, deploy, and scale cutting-edge AI capabilities that redefine how the organization operates, innovates, and delivers value.
- The position combines deep AI engineering leadership with enterprise architecture ownership and innovation stewardship – enabling the development of production-grade AI systems that deliver meaningful, measurable business impact.
- This role operates at the intersection of engineering excellence, forward-looking innovation, and enterprise-scale impact, partnering closely with senior leadership to unlock productivity, accelerate transformation, and establish EXL as a leader in applied AI.
Core Mandate: Innovation · Architecture · Engineering
Engineering-first leadership role with accountability for production-grade AI systems, supported by strong architectural foundations and innovation leadership.
Key Responsibilities
1. Enterprise AI Engineering & Platforms (Foundation)
- Own and evolve EXL's enterprise AI engineering platforms spanning Agentic AI systems, LLM/MLOps, orchestration layers, and enterprise integrations
- Establish rigorous engineering standards to ensure scalability, reliability, security, and cost efficiency
- Drive the full AI lifecycle from discovery and prototyping to deployment, adoption, and value realization
2. AI Architecture & Solution Design (Design Authority)
- Define enterprise-wide AI architecture patterns and reference models
- Ensure alignment across data, cloud infrastructure, security, privacy, and responsible AI principles
- Serve as the technical design authority for complex AI initiatives
3. Innovation & Emerging AI Vigilance (Future Readiness)
- Maintain continuous awareness of emerging AI trends including Agentic AI, autonomous systems, and frontier foundation models
- Enable rapid experimentation (within days, not months) followed by disciplined scaling
- Balance innovation with delivery rigor to avoid experimentation without outcomes
4. Value Realization & Business Outcomes (Impact)
- Translate AI deployments into measurable enterprise outcomes such as productivity gains, cost reduction, and risk mitigation.
- Own adoption and realization metrics, not just solution delivery.
- Partner with operations and functional leaders to embed AI into daily workflows.
5. Talent & Operating Model (Sustainability & Scale)
- Lead and mentor a high-performing AI architecture and engineering organization.
- Establish a federated-but-governed AI operating model across EXL.
- Raise engineering quality, product mindset, and delivery discipline across teams.
Technical & Architecture Expertise (Agentic AI)
- End-to-End AI Engineering Leadership: Proven experience owning the full AI lifecycle – from prototyping to enterprise-scale deployment, optimization, and value realization
- Agentic AI & Modern Frameworks: Strong expertise in multi-agent systems, tool-using agents, and human-in-the-loop designs, with hands-on exposure to frameworks like LangGraph, CrewAI, and similar ecosystems
- Foundation Models & Multimodal AI: Advanced knowledge of LLM platforms (OpenAI, Anthropic/Claude) and exposure to multimodal AI (voice, avatar, video) technologies
- AI-native Tooling & Developer Ecosystem: Familiarity with next-gen AI development and productivity tools such as Cursor, Replit, and copilots
- Enterprise Architecture & Governance: Proven ability to define scalable, secure, and cost-efficient AI architecture and standards across data, cloud, integration, security, and responsible AI
Required Experience & Qualifications
- 15+ years of total experience preferred
- Relevant AI and engineering leadership experience carries more weight than tenure
- Backgrounds from ITES, analytics, AI services firms, enterprise captives, BFSI, or large-scale transformation programs are well suited
- Proven track record of:
- Building and scaling enterprise AI capabilities
- Leading advanced AI initiatives at scale
- Driving AI-linked business outcomes and impact
- Strong understanding of:
- Agentic AI and LLMs architectures
- Data platforms, cloud, security, and compliance
- Enterprise integration and legacy modernization
- Experience engaging with Boards, CEOs, and EC-level stakeholders
Leadership & Behavioral Expectations
- Enterprise-first mindset with strong commercial orientation
- Ability to influence without authority across diverse functions
- Exceptional executive communication and storytelling skills
- Calm, decisive leadership in ambiguity and rapid change
- Deep commitment to responsible AI and ethical deployment
Why This Role Matters to EXL
- This role is central to EXL's evolution into an AI-native enterprise. It will shape durable internal AI capabilities, influence enterprise-wide ways of working, and directly partner with the Global CIO and senior leadership on long-term technology and transformation strategy
