AI Lead

AI Lead - Partner

 ROLES & RESPONSIBILITIES 
AI Strategy Development:
Partner with Audit Technology and Audit leaders to co-create a clear, actionable AI strategy aligned with business goals.
Develop and own a standard AI solution architecture to serve as a guideline/ checklist for all AI developments, covering governance, risk, compliance
Develop roadmap/ pipeline with specific milestones
Build more focus on Multi-Agentic Solutions Development - partner network, customer selling through early engagements and co-design, develop Forward deployment engineers (FDE).
Proven competencies in building business cases and selling and scaling AI solutions in different stakeholder scenarios (e.g. internal functional users/ external customer teams), owning and showcasing  outcomes

Implementation & Control – in collaboration with Audit Tech leadership :
Proven network within tech partner ecosystems, examples of working closely with large AI TSPs like OpenAI, Google, Azure leadership and tech teams, co-development, early access
Access to US start-ups and university ecosystems to gain access to test and build audit-specific solutions on their latest algorithms and model stacks, co-create IPs

Implementation & Control – in collaboration with Audit Tech leadership (Continued) :
Coordinate with IT and other stakeholders for successful implementation of AI technology.
Development of standard practices for risk mitigation and taxonomies, along with large TSPs like Google, Azure, OpenAI partner teams
Take inputs from target user groups and customers e.g. on their perceived risks while developing risk taxonomies, to manage agentic misalignment, agent behavior control, risk/ trust in agent orchestrators, AgentOps for continuous autonomous monitoring and observability
Oversee the governance and control mechanisms for AI implementation, ensuring alignment to KPMG compliance and legal controls as needed.
Workforce Development & AI Adoption.
Lead the setup of the offshore AI center—define structure, roles, workflows, and culture.
Hire top talent across AI/ML, engineering, product, and operations.
Establish agile processes and governance to ensure speed, quality, and accountability.

Develop Talent & Capability
Develop and implement training programs to familiarize the workforce with AI concepts and tools.
Training and certification partnerships with large TSPs like latest models from Google, AWS, Axure, OpenAI, Anthropic, Perplexity etc. 
Develop tech talent groups with strategic IT partners, US start-up’s, US and Indian universities, 
Mentor emerging leaders and foster a culture of experimentation and excellence.
Foster a culture of innovative thinking and openness towards AI adoption.
Monitor and report on levels of AI adoption across the organizations.

 
Deliver Products That Matter
Own the full lifecycle of AI products - Identifying & clearly articulating target customers and user groups and developing persona-focused AI solutions business cases, creating alpha/beta user groups within target customer functions, using their early inputs & feedback in design & dev-test- practice forward deployment engineering/ ship2build
Engaging target power-users into developing & testing solutions and creating IPs, as co-designers, co-patenters
Implement robust practices for scalability, reliability, and performance.

Stakeholder Communication:
Develop high visibility for team and leadership internally (Audit Technology Alliance, US Audit, US Digital & AI)  and externally, within tech partners and talent supply sides and foster seamless AI integration, alignment of objectives and benefits tracking.

Thought leadership:
Maintain and continue to develop AI thought leadership - Early access programs, first port-of-call for tech providers, developing practice guardrails/ checklists, responsible and trusted AI testcase repositories, EVALS
Publish Whitepapers, file for patents, present at various forums, represent KPMG at various industry/technology forums and initiatives.

 ROLES & RESPONSIBILITIES 
AI Strategy Development:
Partner with Audit Technology and Audit leaders to co-create a clear, actionable AI strategy aligned with business goals.
Develop and own a standard AI solution architecture to serve as a guideline/ checklist for all AI developments, covering governance, risk, compliance
Develop roadmap/ pipeline with specific milestones
Build more focus on Multi-Agentic Solutions Development - partner network, customer selling through early engagements and co-design, develop Forward deployment engineers (FDE).
Proven competencies in building business cases and selling and scaling AI solutions in different stakeholder scenarios (e.g. internal functional users/ external customer teams), owning and showcasing  outcomes

Implementation & Control – in collaboration with Audit Tech leadership :
Proven network within tech partner ecosystems, examples of working closely with large AI TSPs like OpenAI, Google, Azure leadership and tech teams, co-development, early access
Access to US start-ups and university ecosystems to gain access to test and build audit-specific solutions on their latest algorithms and model stacks, co-create IPs

Implementation & Control – in collaboration with Audit Tech leadership (Continued) :
Coordinate with IT and other stakeholders for successful implementation of AI technology.
Development of standard practices for risk mitigation and taxonomies, along with large TSPs like Google, Azure, OpenAI partner teams
Take inputs from target user groups and customers e.g. on their perceived risks while developing risk taxonomies, to manage agentic misalignment, agent behavior control, risk/ trust in agent orchestrators, AgentOps for continuous autonomous monitoring and observability
Oversee the governance and control mechanisms for AI implementation, ensuring alignment to KPMG compliance and legal controls as needed.
Workforce Development & AI Adoption.
Lead the setup of the offshore AI center—define structure, roles, workflows, and culture.
Hire top talent across AI/ML, engineering, product, and operations.
Establish agile processes and governance to ensure speed, quality, and accountability.

Develop Talent & Capability
Develop and implement training programs to familiarize the workforce with AI concepts and tools.
Training and certification partnerships with large TSPs like latest models from Google, AWS, Axure, OpenAI, Anthropic, Perplexity etc. 
Develop tech talent groups with strategic IT partners, US start-up’s, US and Indian universities, 
Mentor emerging leaders and foster a culture of experimentation and excellence.
Foster a culture of innovative thinking and openness towards AI adoption.
Monitor and report on levels of AI adoption across the organizations.

Deliver Products That Matter
Own the full lifecycle of AI products - Identifying & clearly articulating target customers and user groups and developing persona-focused AI solutions business cases, creating alpha/beta user groups within target customer functions, using their early inputs & feedback in design & dev-test- practice forward deployment engineering/ ship2build
Engaging target power-users into developing & testing solutions and creating IPs, as co-designers, co-patenters
Implement robust practices for scalability, reliability, and performance.

Stakeholder Communication:
Develop high visibility for team and leadership internally (Audit Technology Alliance, US Audit, US Digital & AI)  and externally, within tech partners and talent supply sides and foster seamless AI integration, alignment of objectives and benefits tracking.

Thought leadership:
Maintain and continue to develop AI thought leadership - Early access programs, first port-of-call for tech providers, developing practice guardrails/ checklists, responsible and trusted AI testcase repositories, EVALS
Publish Whitepapers, file for patents, present at various forums, represent KPMG at various industry/technology forums and initiatives.

Mandatory  technical & functional skills
Skilled on Agentic and Agent GRC
Tech: Multi-agent, multi-protocol, multi-cloud e.g. between AWS Agentcore and Google, Anthropic, Perplexity. 
Dev-GRC: Forward engineering, early customer engagement- testing & feedback, agent behavior monitoring, agentic misalignment mgt- checklists, extreme testcase portfolios
Branding & packaging standardized interfaces on agentic solution stacks, with trusted GRC guidelines and reports
Excellent communication skills and the ability to simplify complex concepts.

 This role is for you if you have  the below
Educational qualifications –

A combination of Degree in business management, computer science, data science or related AI field.

Work experience
7-10+ yrs experience years of proven experience with strong AI solutioning/ selling/ financial services background, with experience building global teams. 
Proven success in developing and deploying AI products in enterprise environments with Deep understanding of AI/ML technologies, product development, and agile delivery.
Strong strategic thinking.
Excellent storytelling, stakeholder engagement, and change leadership skills.

Experience Level

Senior Level