Senior Engagement Manager

Key Responsibilities 

Client Leadership & Executive Engagement 

• Build trusted relationships with client executives and senior business, data, digital, operations, engineering, supply chain, and technology leaders. 

• Independently lead steering committees, quarterly business reviews, transformation workshops, roadmap discussions, and executive working sessions. 

• Translate business priorities and operational challenges into analytics, data, AI, and digital transformation initiatives. 

• Present complex findings, recommendations, and investment cases through clear executive storytelling and data-driven narratives. 

• Act as the primary client-facing leader for strategic engagements and maintain alignment across client and EXL leadership teams. 

Manufacturing & Automotive Transformation 

• Lead analytics and AI programs across manufacturing operations, supply chain, procurement, logistics, production planning, demand planning, and inventory optimization. 

• Shape solutions for quality analytics, warranty analytics, connected manufacturing, engineering analytics, plant performance, digital manufacturing, and industrial AI. 

• Identify high-value use cases supporting throughput, productivity, quality, cost, service, working capital, asset performance, safety, and sustainability outcomes. 

• Connect business priorities with practical operating-model, process, data, analytics, and technology interventions. 

Data & AI Transformation 

• Define enterprise analytics and AI strategies, transformation roadmaps, and prioritized use-case portfolios. 

• Lead data-platform modernization, cloud migration, data engineering, data management, governance, quality, integration, and analytics enablement initiatives. 

• Guide solutions across descriptive, predictive, prescriptive, optimization, simulation, forecasting, root-cause analysis, and operational intelligence use cases. 

• Enable machine learning, generative AI, agentic AI, and decision-intelligence solutions through scalable and governed data foundations. 

• Partner with architects, engineers, data scientists, and business teams to ensure solutions are secure, scalable, adoptable, and tied to measurable outcomes. 

Solutioning & Business Development 

• Lead solution design and consulting engagements for both focused initiatives and complex multi-workstream transformation programs. 

• Own or contribute to proposals, RFPs, RFIs, statements of work, executive pitches, and deal-shaping discussions. 

• Develop transformation roadmaps, delivery approaches, staffing models, workplans, effort estimates, cost estimates, assumptions, dependencies, and risks. 

• Present differentiated solutions to executive stakeholders and guide opportunities from qualification through closure and transition to delivery. 

• Collaborate with sales, account, industry, capability, architecture, and delivery leaders to expand strategic client relationships. 

Account Growth & Commercial Leadership 

• Provide independent leadership for client portfolios and engagements valued up to $10M-$15M annually. 

• Develop account growth strategies and identify cross-sell and upsell opportunities across analytics, data, AI, GenAI, and transformation services. 

• Build executive relationships across multiple client functions and create a forward-looking opportunity pipeline. 

• Apply strong financial and commercial discipline to scope, pricing, margins, staffing, utilization, and delivery commitments. 

Delivery Leadership 

• Provide executive oversight across multiple programs and workstreams from discovery through implementation and managed delivery. 

• Establish program governance, monitor risks and dependencies, and drive timely resolution of delivery and stakeholder issues. 

• Ensure high-quality outcomes, strong customer satisfaction, effective resource planning, and disciplined performance management. 

• Mentor delivery managers, engagement leads, solution architects, analytics leaders, and technical teams. 

Capability Building & Innovation 

• Build and scale Manufacturing Analytics, Data, AI, and GenAI capabilities, solutions, and reusable assets. 

• Develop industry-specific frameworks, maturity assessments, accelerators, reference architectures, case studies, and points of view. 

• Contribute to hiring, team building, talent development, competency planning, and communities of practice. 

• Drive thought leadership and innovation across smart manufacturing, connected operations, digital thread, digital twins, industrial data, and AI-enabled decision-making.