SrAVP-Senior Engagement Manager

Job description

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.

Qualifications

- Required Experience & Qualifications

- 12-18 years of experience across analytics, data, AI, digital transformation, management consulting, or technology-enabled business transformation.

- At least five years of client-facing leadership experience across analytics, data, AI, or transformation engagements.

- Proven ability to independently manage strategic client relationships and portfolios or engagements valued up to $10M-$15M annually.

- Experience leading executive discussions, steering committees, transformation workshops, roadmap development, and solution presentations.

- Demonstrated ability to create compelling executive stories that connect data and analytical insights to business priorities and financial outcomes.

- Strong understanding of the end-to-end data and AI lifecycle, including data engineering, data management, cloud data platforms, business intelligence, advanced analytics, machine learning, generative AI, deployment, governance, and adoption.

- Experience leading proposals, RFPs, solution architecture, staffing, effort estimation, cost estimation, commercial inputs, and transition planning.

- Ability to lead multidisciplinary teams across business consulting, data engineering, analytics, AI, architecture, program management, and change enablement.

- Bachelor’s or master’s degree in engineering, computer science, data, analytics, operations, business, or a related discipline.

Industry Experience

- Preferred experience in Manufacturing Analytics, Automotive, Mobility, Industrial Manufacturing, Heavy Equipment, Industrial Products, Aerospace, Transportation, or related manufacturing-intensive sectors.

- Automotive OEM, Tier 1 supplier, connected vehicle, manufacturing engineering, plant operations, supply chain, quality, warranty, or aftersales experience is highly desirable.

- Experience working with large, complex global manufacturers or industrial enterprises with distributed plants, functions, and technology environments.

Preferred Qualifications

- Experience supporting organizations such as automotive OEMs, automotive suppliers, industrial manufacturers, equipment manufacturers, or engineering-intensive enterprises.

- Experience with Azure, AWS, GCP, Databricks, Snowflake, Microsoft Fabric, Power BI, Tableau, or comparable data and analytics ecosystems.

- Exposure to smart manufacturing, Industry 4.0, connected factory, digital thread, digital twins, predictive maintenance, industrial IoT, and manufacturing execution environments.

- Experience shaping or leading GenAI use cases in engineering, manufacturing, supply chain, quality, warranty, service, knowledge management, or commercial operations.

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- Experience building an industry offering, center of excellence, reusable assets, strategic partnerships, or high-performing multidisciplinary teams.

Leadership Competencies

- Executive presence and trusted-advisor mindset

- Consultative selling and commercial orientation

- Executive storytelling, influence, and presentation capability

- Manufacturing and operational business acumen

- Strategic thinking with strong execution discipline

- Financial acumen and account-growth mindset