We are looking for an experienced Engagement Manager - AI & Analytics Consulting to lead end-to-end AI and analytics consulting engagements, manage strategic client relationships, and ensure successful delivery of complex data and analytics initiatives.

The role will combine consulting, engagement management, delivery governance, stakeholder management, pre-sales, and account growth responsibilities. The ideal candidate should be comfortable working with senior business and technology stakeholders and possess a strong understanding of modern data and analytics ecosystems across cloud platforms such as AWS, Azure, and GCP.

Key Responsibilities:

Engagement & Client Management:

- Own and manage end-to-end client engagements from initiation through successful delivery.

- Build and maintain strong relationships with senior client stakeholders and decision-makers.

- Understand client business objectives, challenges, and strategic priorities.

- Translate business requirements into actionable AI, analytics, and data solutions.

- Act as the primary escalation point for engagement-related issues.

- Conduct regular client reviews and communicate project progress, risks, dependencies, and outcomes.

- Ensure high levels of client satisfaction and successful engagement outcomes.

AI & Analytics Consulting:

- Lead consulting initiatives across AI, analytics, data engineering, and modern data platforms.

- Identify opportunities where AI and analytics can create measurable business value.

- Define solution approaches, engagement roadmaps, and delivery strategies.

- Guide teams in developing scalable analytics and AI solutions.

- Evaluate existing data and analytics environments and recommend modernization opportunities.

- Work with technical teams to ensure proposed solutions align with business objectives and enterprise architecture.

Delivery Management & Governance:

- Provide overall leadership and governance for multiple AI and analytics projects.

- Ensure projects are delivered within agreed timelines, scope, quality, and budget.

- Define project milestones, deliverables, dependencies, and success criteria.

- Establish delivery governance mechanisms, review processes, and operational standards.

- Monitor project risks, issues, assumptions, and dependencies and drive timely resolution.

- Ensure appropriate resource allocation across engagements.

- Work closely with delivery leads, architects, data engineers, data scientists, and analytics teams.

- Drive Agile/Scrum practices across project teams where applicable.

Requirements & Solution Definition:

- Lead business requirement gathering and discovery workshops.

- Engage with business and technology stakeholders to understand current-state challenges.

- Define business problems, analytical objectives, KPIs, and expected outcomes.

- Convert business requirements into high-level solution and delivery plans.

- Collaborate with solution architects and engineering teams to develop scalable solutions.

- Ensure alignment between business requirements and technical implementation.

Pre-Sales & Business Development:

- Support pre-sales activities for AI, analytics, and data consulting opportunities.

- Identify new opportunities within existing and prospective client accounts.

- Participate in client presentations, discovery sessions, workshops, and solution discussions.

- Develop proposals, solution approaches, estimates, and delivery plans.

- Contribute to RFP/RFI responses and proposal development.

- Define and review Statements of Work (SOWs), scope, assumptions, deliverables, and commercials in collaboration with relevant teams.

- Partner with sales teams to convert consulting opportunities into successful engagements.

Account Growth:

- Identify opportunities to expand existing client engagements.

- Build relationships across business units and identify additional analytics and AI use cases.

- Develop account strategies in collaboration with sales and delivery leadership.

- Drive cross-selling and expansion opportunities across AI, analytics, data engineering, and cloud transformation.

- Maintain a strong understanding of client priorities and emerging business requirements.

Technology & Data Landscape:

- Maintain a strong understanding of modern data and analytics ecosystems.

- Work with teams using cloud platforms such as AWS, Azure, and GCP.

- Understand modern data platforms and technologies including Databricks and Snowflake.

- Provide consulting guidance around data engineering, analytics platforms, data pipelines, and AI initiatives.

- Understand data architecture, data governance, cloud analytics, and enterprise data transformation concepts.

- Stay updated on emerging AI, analytics, and data technologies and their business applications.

Stakeholder Management:

- Manage relationships with CXO-level, business, technology, and functional stakeholders.

- Facilitate discussions between business stakeholders and technical teams.

- Communicate complex technical concepts in a clear business-oriented manner.

- Build consensus across diverse stakeholder groups.

- Proactively manage expectations, escalations, and delivery concerns.

Team Leadership:

- Lead and mentor cross-functional AI and analytics teams.

- Provide direction to project managers, consultants, data engineers, data scientists, and analytics professionals.

- Promote collaboration and knowledge sharing across teams.

- Support capability development and identify skill gaps.

- Encourage adoption of industry best practices and standardized delivery methodologies.

Required Skills & Experience:

- 10 - 15 years of overall experience in technology consulting, analytics, data, AI, or related domains.

- Strong experience in engagement management and client-facing consulting roles.

- Proven experience managing end-to-end technology or analytics engagements.

- Strong understanding of AI, analytics, data engineering, and modern data platforms.

- Experience working with enterprise clients and senior stakeholders.

- Strong pre-sales and business development exposure.

- Experience in proposal development, RFP/RFI responses, and SOW preparation.

- Strong delivery governance and project management skills.

- Experience with Agile/Scrum methodologies.

- Strong understanding of cloud platforms such as AWS, Azure, and GCP.

- Working knowledge of Databricks and Snowflake.

- Strong stakeholder management, communication, negotiation, and presentation skills.

- Ability to manage multiple priorities and complex client engagements.

Preferred Qualifications:

- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, Business, Analytics, or a related discipline.

- Experience in AI/ML, data analytics, data engineering, or digital transformation consulting.

- Experience managing large enterprise accounts.

- Exposure to cloud migration and data modernization programs.

- Experience in building and growing strategic client relationships.

- Experience managing geographically distributed teams.