Engagement Manager – Data & AI

Engagement Manager Data & AI

Experience : 15 -18 years

Location : Bangalore

Role Summary

The Engagement Manager will act as the single point of contact (SPOC) from the Data & AI practice for regional sales and account teams, supporting presales, solutioning, and delivery governance. This role bridges business and technology, ensuring that solutions are well-structured, proposals are compelling, and deliveries adhere to best practices. The individual will bring strong travel domain expertise, a solid understanding of Data & AI, and the ability to translate business needs into scalable solutions.

Responsibilities

Presales & Solution Support

• Sales Enablement: Partner with regional sales and account teams to identify and shape Data & AI opportunities.
• Solutioning: Collaborate with technical teams to define solution approaches, architecture, and scope aligned with client needs.
• Proposal Development: Contribute to RFP responses, proposals, and effort estimations.
• Pitch Support: Create and deliver high-impact presentations and solution walkthroughs to support deal pursuits.

Delivery Governance & Oversight

• Delivery Alignment: Ensure projects are executed in line with defined architectures, best practices, and quality standards.
• Program Oversight: Provide governance across engagements, tracking progress, risks, and dependencies.
• Issue Resolution: Act as an escalation point to resolve delivery challenges in collaboration with delivery teams.
• Best Practices: Drive adoption of standard methodologies, reusable assets, and frameworks across engagements.

Practice Representation

• SPOC for Practice: Act as the primary interface between the Data & AI practice and regional teams.
• Capability Positioning: Help position the practices capabilities across Data Engineering, BI, and AI/ML in relevant opportunities.
• Internal Alignment: Ensure seamless coordination between sales, account teams, and delivery units.

Domain & Advisory Support

• Travel Domain Expertise: Provide contextual insights and guidance for airline/travel use cases (e.g., revenue management, customer analytics, operations).
• Use Case Definition: Help shape problem statements and define high-value Data & AI use cases.
• Emerging Trends: Bring awareness of trends such as cloud data platforms and Generative AI to enhance solution relevance.

Asset & Capability Development

• Reusable Assets: Contribute to development of pitch decks, case studies, solution frameworks, and accelerators.
• Knowledge Sharing: Support capability building within the practice and across regional teams.

Requirements

Education and Experience

• Bachelors degree in Engineering, Technology, or related field; MBA preferred.
• 1520 years of experience in consulting, presales, or delivery roles within Data & AI or related domains.

Domain & Technical Skills

• Strong domain knowledge in airlines, travel, or transportation.
• Conceptual understanding of:
• Data Engineering (data pipelines, data platforms)
• Data Warehousing & BI (reporting, dashboards, analytics)
• AI/ML (predictive analytics, ML lifecycle)
• Hands-on experience in at least one area (Data Engineering, BI, or AI/ML).
• Awareness of cloud ecosystems and emerging trends such as Generative AI.

Core Competencies

• Stakeholder Management: Ability to work effectively with sales, account teams, and delivery units across regions.
• Communication: Strong verbal and written communication skills, with the ability to simplify complex concepts.
• Presentation Skills: Proven ability to create compelling, executive-level presentations and storytelling decks.
• Consultative Thinking: Ability to translate business needs into structured solution approaches.
• Program Oversight: Experience in managing multiple engagements, risks, and dependencies.

Additional Requirements

• Willingness to travel to client locations globally for short-term assignments (23 weeks at a time).

Preferred Qualifications

• Experience in IT services or consulting organizations.
• Exposure to large-scale data transformation or AI-led programs in the travel domain.
• Familiarity with estimation models, solutioning frameworks, and commercial constructs.