Job Description

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Function Consulting

Position Senior Manager

Title AI/GenAI– Senior Manager

Position Full Time

Educational qualification BTech/Masters/PhD

The opportunity

We are seeking an experienced GenAI Senior Manager with 12+ years of overall experience, including significant hands-on and leadership expertise in Generative AI, Agentic AI, RAG architectures, Conversational AI, AI agents, Copilot solutions, enterprise AI platforms, and AI governance. The ideal candidate will lead the strategy, architecture, delivery, governance, and enterprise-wide scaling of AI solutions while managing multi-disciplinary teams of AI engineers, data scientists, solution architects, platform engineers, and business stakeholders.

The role requires a strong blend of technical leadership, enterprise solution architecture, AI strategy, program delivery, stakeholder management, people leadership, quality governance, and business value realization to drive large-scale adoption of GenAI capabilities. The candidate should have proven experience delivering AI-powered solutions such as RAG applications, AI agents, copilots, enterprise knowledge management platforms, AI automation workflows, multi-agent systems, intelligent search, and AI-enabled business transformation programs, while ensuring Responsible AI, quality, security, compliance, scalability, and operational excellence standards are met.

The individual will lead enterprise AI quality, validation, observability, and governance initiatives to ensure the reliability, security, performance, scalability, and business effectiveness of AI and GenAI solutions while partnering with senior technical, business, architecture, security, compliance, and executive stakeholders.

Important: Hands-on experience delivering AI solutions in enterprise or production environments is required. Certifications, personal projects, and demos alone are not sufficient.

Your key responsibilities

• Lead the strategy, design, development, and delivery of enterprise AI, GenAI, Agentic AI, Conversational AI, Copilot, and RAG-based solutions aligned with business and technology objectives.
• Define enterprise AI strategy, roadmaps, governance frameworks, reference architectures, operating models, delivery standards, and capability development plans to enable scalable AI adoption across the organization.
• Drive the architecture, implementation, and industrialization of AI platforms, copilots, multi-agent systems, conversational AI solutions, intelligent automation workflows, enterprise search, and knowledge management solutions.
• Collaborate with senior business stakeholders and executive sponsors to identify high-value AI use cases, prioritize initiatives, establish success metrics, and realize measurable business value.
• Oversee the end-to-end AI solution lifecycle, including use case discovery, feasibility assessment, solution architecture, data readiness, development, testing, deployment, monitoring, adoption, optimization, and continuous improvement.
• Lead, mentor, and manage cross-functional teams of AI engineers, data scientists, architects, developers, platform engineers, and business analysts, fostering innovation, engineering excellence, and delivery discipline.
• Establish and enforce best practices for Responsible AI, AI security, privacy, compliance, risk management, explainability, model governance, and ethical AI adoption across enterprise AI implementations.
• Drive adoption of enterprise AI capabilities leveraging Azure AI Foundry, Azure OpenAI, OpenAI, Databricks, Microsoft Copilot ecosystem, vector databases, enterprise search platforms, and modern AI orchestration frameworks.
• Ensure AI solutions are scalable, reliable, secure, cost-optimized, observable, maintainable, and aligned with enterprise architecture, cloud, data, security, and governance standards.
• Partner with engineering, data, security, risk, and business teams to define evaluation frameworks, quality benchmarks, guardrails, observability standards, and performance metrics for AI systems.
• Guide the implementation of RAG architectures, embedding strategies, retrieval pipelines, vector databases, knowledge ingestion frameworks, grounding mechanisms, and agentic workflows to enhance productivity and decision-making.
• Manage stakeholder communication, executive reporting, program governance, budgeting, resource planning, risk management, vendor coordination, delivery assurance, and benefits realization for AI programs.
• Stay current with emerging trends in GenAI, Agentic AI, multimodal AI, AI agents, autonomous workflows, LLMOps, AI governance, and enterprise AI platforms to drive innovation and competitive advantage.
• Contribute to practice development through reusable accelerators, reference architectures, estimation models, delivery playbooks, solution frameworks, thought leadership, and capability building initiatives.
• Drive AI solution quality through structured validation, model evaluation, regression testing, hallucination assessment, prompt quality reviews, security assessments, and production readiness checks.
• Support pre-sales, solution shaping, client conversations, capability presentations, proposal inputs, and executive-level AI transformation discussions as required.

Skills and Attributes:

Professional Experience

• 12+ years of overall experience, including 6+ years leading AI/ML, GenAI, data, analytics, automation, or digital transformation initiatives in enterprise environments.
• Proven experience delivering, operationalizing, and scaling production-grade AI, GenAI, Agentic AI, Copilot, Conversational AI, and RAG-based solutions from concept through deployment, monitoring, adoption, and business value realization.
• Strong understanding of enterprise AI architecture and hands-on exposure to multiple areas, including:
• LLM and GenAI application development
• RAG architectures and enterprise knowledge management solutions
• Agentic AI, AI agents, and multi-agent systems
• Conversational AI, chatbot, virtual assistant, and Copilot solutions
• Prompt engineering, prompt optimization, and prompt lifecycle management
• AI evaluation, model validation, safety testing, guardrails, and Responsible AI
• AI governance, risk management, compliance, privacy, and security controls
• AI platform engineering and cloud-native AI deployments
• MLOps / LLMOps and operationalization of AI solutions
• Data engineering, vector databases, embeddings, semantic search, and retrieval pipelines
• AI observability, monitoring, cost optimization, performance tuning, and production support
• Integration of AI solutions with enterprise applications, APIs, workflows, and business processes
• Demonstrated ability to lead large cross-functional teams of AI engineers, architects, data scientists, developers, platform engineers, testers, and business analysts across multiple workstreams.
• Strong stakeholder management skills with experience translating complex business needs into scalable AI solutions, delivery roadmaps, operating models, and measurable business outcomes.
• Experience with enterprise AI platforms such as Azure AI Foundry, Azure OpenAI, OpenAI, Databricks, Microsoft Copilot, Microsoft Power Platform, enterprise search platforms, and related AI ecosystems.
• Experience managing AI programs with responsibilities across delivery governance, solution assurance, budgeting, resource planning, executive reporting, risk management, and stakeholder communication.
• Ability to contribute to AI practice development, capability building, reusable assets, accelerators, proposal support, solution blueprints, and thought leadership.

Educational Background

• Bachelor’s/master’s degree in computer science, Data Science, Artificial Intelligence, Machine Learning, Engineering, Information Technology, or related field.
• Advanced certifications in Azure AI, Azure OpenAI, Databricks, cloud platforms, data engineering, AI/ML, enterprise architecture, or project/program management will be an added advantage.

Technical Skills

• Strong understanding of Large Language Models (LLMs), Generative AI, Agentic AI, AI Agents, Multi-Agent Systems, Conversational AI, Copilot solutions, and RAG architectures.
• Proven experience designing, delivering, and scaling enterprise-grade GenAI, Copilot, Conversational AI, AI Agent, knowledge management, and intelligent automation solutions.
• Experience defining AI strategy, enterprise solution roadmaps, architecture standards, governance models, delivery methodologies, reusable patterns, and operating models.
• Strong knowledge of AI platform ecosystems including Azure AI Foundry, Azure OpenAI, OpenAI APIs, Databricks, Vector Databases, Enterprise Search platforms, Microsoft Copilot ecosystem, and cloud-native AI services.
• Experience leading the design and implementation of RAG pipelines, embedding models, retrieval strategies, vector indexing, knowledge ingestion, content enrichment, semantic search, and AI-powered business applications.
• Understanding of AI evaluation, prompt testing, response quality measurement, hallucination detection, guardrails, red-teaming, AI observability, quality metrics, and Responsible AI practices.
• Experience establishing governance frameworks covering AI security, privacy, compliance, intellectual property protection, model risk, data protection, safety, ethical AI, and regulatory alignment.
• Strong knowledge of prompt engineering, prompt orchestration, agent orchestration frameworks, function calling, tool integrations, memory management, workflow automation, and human-in-the-loop patterns.
• Experience managing the end-to-end AI lifecycle, including ideation, discovery, feasibility analysis, architecture, development, validation, deployment, monitoring, optimization, support, and adoption.
• Proven ability to lead, mentor, and coach AI engineers, architects, data scientists, platform engineers, developers, and cross-functional delivery teams.
• Experience integrating AI solutions with enterprise applications, APIs, databases, data lakes, cloud platforms, DevOps pipelines, workflow systems, security services, and business processes.
• Strong understanding of MLOps, LLMOps, CI/CD for AI applications, model monitoring, prompt/version management, evaluation pipelines, performance optimization, traceability, and operationalization of AI solutions.
• Ability to work with executive stakeholders to identify AI opportunities, define value cases, build business justification, prioritize investments, and drive adoption across business functions.
• Experience with enterprise architecture, software engineering best practices, API-first design, microservices, cloud architecture, event-driven architecture, scalability, reliability, and secure solution design.
• Strong analytical, problem-solving, decision-making, stakeholder management, communication, executive reporting, and consultative leadership skills.
• Knowledge of emerging AI areas such as multimodal AI, autonomous agents, synthetic data, AI-assisted software engineering, AI governance platforms, enterprise copilots, and domain-specific AI assistants.
• Experience in estimating AI initiatives, defining delivery plans, managing dependencies, assessing technical risks, and ensuring successful transition from prototype to production.

Soft Skills

• Excellent problem-solving, strategic thinking, and decision-making skills, with the ability to translate AI capabilities into measurable business outcomes and enterprise value.
• Strong communication, stakeholder management, executive presentation, and consultative leadership skills, with the ability to influence technical teams, business leaders, senior executives, and external stakeholders.
• Ability to manage ambiguity, prioritize competing demands, drive alignment across teams, and lead complex AI transformation programs in fast-paced enterprise environments.
• Strong people leadership skills with the ability to mentor teams, build capabilities, manage performance, encourage innovation, and create a culture of engineering excellence and responsible AI adoption.
• Ability to balance hands-on technical depth with senior-level program ownership, business engagement, delivery governance, and strategic advisory responsibilities.

Other Responsibilities:

• Lead the delivery of enterprise GenAI, Agentic AI, Conversational AI, Copilot, and RAG solutions, from ideation through architecture, development, deployment, monitoring, optimization, and business adoption.
• Define AI strategy, solution roadmaps, reusable architectures, governance frameworks, delivery playbooks, quality standards, and best practices to drive scalable enterprise AI adoption.
• Partner with business, technology, data, security, risk, compliance, and executive stakeholders to identify opportunities, prioritize AI use cases, shape solution approaches, and deliver measurable business value.
• Mentor, manage, and lead cross-functional teams of AI engineers, architects, data scientists, developers, platform engineers, and analysts, ensuring delivery excellence, innovation, and continuous improvement.
• Drive AI governance, Responsible AI, solution quality, security, compliance, privacy, operational readiness, and risk management across all AI initiatives.
• Establish evaluation frameworks for AI outputs, including accuracy, relevance, groundedness, bias, toxicity, explainability, latency, cost, reliability, and user adoption metrics.
• Oversee production readiness, release governance, monitoring, incident management, support transition, and ongoing optimization of enterprise AI solutions.
• Contribute to capability building through training, mentoring, knowledge sharing, reusable accelerators, technical assets, solution blueprints, and AI community initiatives.
• Support leadership in building AI service offerings, solution propositions, estimation models, delivery approaches, and executive-level presentations for GenAI transformation programs.

Why Join Us

• Be at the forefront of AI-driven innovation across multiple client sectors.
• Work with global clients to drive real business impact.
• Collaborate with a team of AI experts, analytics leaders, and industry specialists in a highly entrepreneurial environment.

What we offer

EY Global Delivery Services (GDS) is a dynamic and truly global delivery network. We work across six locations – Argentina, China, India, the Philippines, Poland and the UK – and with teams from all EY service lines, geographies and sectors, playing a vital role in the delivery of the EY growth strategy. From accountants to coders to advisory consultants, we offer a wide variety of fulfilling career opportunities that span all business disciplines. In GDS, you will collaborate with EY teams on exciting projects and work with well-known brands from across the globe. We’ll introduce you to an ever-expanding ecosystem of people, learning, skills and insights that will stay with you throughout your career.

• Continuous learning You’ll develop the mindset and skills to navigate whatever comes next.
• Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.
• Transformative leadership We’ll give you the insights, coaching and confidence to be the leader the world needs.
• Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs.

EY | Building a better working world

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.