COE Lead - Artificial Intelligence
Worldhire Global
Posted by a Verified Recruiter
Industry
FinTech & Payments
Location
Delhi, India
Work mode
On-site
Job type
Full-time
Annual salary
₹40,00,000 - ₹60,00,000 (₹40 Lakh - ₹60 Lakh)
Minimum experience
8+ years
Posted
5th August, 2026
Required skills
Generative AILLMsPrompt EngineeringRAG ArchitecturesAgentic SystemsAI LifecycleCross-Functional Team LeadershipStakeholder ManagementOpenAIAnthropicAzure OpenAIGoogle Vertex AIAWS Bedrock
About the company
WorldHire helps organizations access top global talent through leadership hiring, specialist recruitment, contract staffing, and cross-border search. With KORUM, we are building a trusted talent discovery platform that enables professionals to be discovered discreetly and helps companies find the right expertise faster and more effectively.
About the role
COE Lead - AI | Job Description
JOB DESCRIPTION
COE Lead - Artificial Intelligence
Role Overview
The COE Lead - Artificial Intelligence is a senior strategic and hands-on leadership role responsible for driving the
organisation's AI transformation agenda. The incumbent will conduct a comprehensive study of all business
functions, identify high-impact opportunities for Agentic AI, Generative AI and broader AI adoption, design the
implementation roadmap, and govern execution across the enterprise. This role sits at the intersection of
technology, business strategy, and change management, and requires deep expertise in Generative AI
frameworks, LLM ecosystems, and enterprise-scale deployment.
Strategic Mandate
The COE Lead AI will be accountable for the following strategic outcomes:
- Establish and operate the AI Center of Excellence as the primary knowledge and delivery engine for AI
initiatives across the organisation.
- Conduct structured AI readiness and opportunity assessments across all business functions including
Finance, HR, ATM Ops, Sales, Tech, Marketing & Customer Service
- Build a prioritised pipeline of AI use cases ranked by business value, feasibility, and strategic alignment.
- Define and enforce AI governance standards, ethical AI practices, and risk management frameworks.
- Act as the primary interface between business stakeholders and technology teams to translate AI
opportunities into executable programs.
Key Responsibilities
1. AI Opportunity Discovery & Business Analysis
- Conduct in-depth assessments of workflows, pain points, and data assets across all organisational
functions to identify viable AI use cases.
- Develop a standardised AI opportunity canvas and scoring model for consistent evaluation of use cases.
- Interview senior stakeholders, process owners, and domain experts to surface latent transformation
opportunities.
- Map existing technology landscape to identify integration points and gaps for AI enablement.
COE Lead - AI | Job Description
Page 2
2. Generative AI Strategy & Roadmap
- Design a multi-horizon GenAI strategy covering quick wins (0-6 months), medium-term pilots (6-18
months), and long-term transformation programs.
- Evaluate and recommend foundation models, LLM platforms (e.g., OpenAI GPT, Anthropic Claude, Google
Gemini, Meta LLaMA, Mistral), and deployment approaches (SaaS, fine-tuned, RAG-based, agentic).
- Define the AI architecture blueprint including model selection, vector databases, embedding strategies,
prompt engineering standards, and agent orchestration frameworks.
- Develop a responsible AI policy covering data privacy, bias mitigation, explainability, and regulatory
compliance.
3. COE Operations & Governance
- Build and lead a cross-functional COE team comprising AI engineers, data scientists, ML Ops engineers,
and business analysts.
- Establish COE operating rhythms including sprint planning, use-case reviews, steering committee
reporting, and retrospectives.
- Create reusable AI accelerators, prompt libraries, RAG pipelines, evaluation frameworks, and toolkits for
scaling deployments.
- Define KPIs and success metrics for all AI initiatives; maintain dashboards for leadership visibility.
4. Implementation & Delivery Oversight
- Lead proof-of-concept design, prototype development, and production deployment of priority AI solutions.
- Oversee MLOps practices including model versioning, monitoring, drift detection, and retraining pipelines.
- Partner with IT, InfoSec, Legal, and Compliance to ensure AI systems meet enterprise security and
regulatory standards.
- Manage vendor relationships with AI platform providers, system integrators, and research partners.
5. Capability Building & Change Management
- Design and execute AI literacy programs and advanced training curricula for business users, data teams,
and leadership.
- Champion a culture of experimentation, continuous learning, and data-driven decision-making.
- Facilitate internal communities of practice for AI/ML, sharing learnings and promoting reuse.
- Develop communication frameworks to manage change, address AI adoption resistance, and build
organisational confidence.
Qualifications & Experience
Mandatory Requirements
- Minimum 5 years of hands-on experience specifically in Generative AI, including LLMs, prompt
engineering, RAG architectures, and agentic systems.
- Proven track record of delivering enterprise-scale AI/ML solutions across multiple business domains.
- Strong understanding of the end-to-end AI lifecycle: ideation, data preparation, model development,
deployment, monitoring, and iteration.
- Experience leading cross-functional teams and managing senior stakeholder relationships.
COE Lead - AI | Job Description
Page 3
- Deep familiarity with at least two major GenAI platforms or APIs (e.g., OpenAI, Anthropic, Azure OpenAI,
Google Vertex AI, AWS Bedrock).
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or a related engineering
discipline.
- Experience establishing or scaling an AI/ML COE or innovation lab within a large enterprise.
- Knowledge of multi-modal AI systems including text, image, audio, and video models.
- Exposure to AI regulation frameworks such as India's AI governance guidelines, or ISO/IEC 42001.
- Publications, patents, or significant contributions to open-source AI projects are a strong advantage.
Technical Competencies
Area
Skills & Tools
GenAI Platforms
OpenAI GPT, Anthropic Claude, Google Gemini, Meta LLaMA, Mistral, Cohere,
Azure OpenAI
Leadership & Behavioural Competencies
- Strategic Vision: Ability to synthesise complex technical possibilities into a coherent, business-aligned AI
strategy.
- Influencing Without Authority: Skilled at building consensus and driving adoption across business units
without direct reporting lines.
- Executive Communication: Proficiency in presenting AI strategies, ROI frameworks, and risk
assessments to C-suite and board audiences.
- Innovation Mindset: Demonstrated curiosity, hypothesis-driven thinking, and comfort with ambiguity and
rapid iteration.
- Ethical Leadership: Strong commitment to responsible AI development, transparency, and inclusive
design principles.
- Talent Development: Experience mentoring AI professionals and building high-performing, diverse
technical teams.
Key Performance Indicators
- Number of AI use cases identified, piloted, and scaled to production within 12 months.
- Measurable business value delivered (cost savings, revenue uplift, efficiency gains) attributed to AI
programs.
- AI adoption rate across business functions (% of employees using AI-enabled tools).
- Time-to-value for AI pilots (idea to production readiness).
- Stakeholder satisfaction scores from business unit leads and the Executive Committee.
- Reduction in manual effort (FTE hours saved) through AI automation initiatives.
- Growth in internal AI talent capability (training completions, certifications, community participation).
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