AI Delivery Lead

EXL

. Lead end-to-end delivery of Agentic AI and Generative AI initiatives from discovery and solutioning through deployment, adoption, and production support .

Posted 9/29/2026full-timeJersey City • New Jersey • United StatesSenior💰 $170,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in leading AI and data modernization initiatives, with a strong focus on cloud transformation, data governance, and responsible AI practices. Proven ability to manage cross-functional teams and deliver enterprise-level solutions in compliance with industry standards.

Highest-signal resume keywords

AI Transformation RoadmapsData GovernanceCloud-Native DesignP&C Insurance ExperienceGenerative AI Solutions

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ModernizationData ManagementData EngineeringMLOpsDevOpsETL/ELT DeliveryAPIsData QualityData LineageRisk Management

Soft Skills

Executive CommunicationClient ManagementSolutioningEstimationGovernance

Tools & Technologies

AWS CloudGuidewireDuck CreekData LakesData WarehousesAnalytics EcosystemsEvent-Driven IntegrationContainerizationInfrastructure as CodeObservability

Certifications & Qualifications

PMPSAFeScrumAWS Solutions ArchitectAWS Data EngineerAWS Machine Learning

Industry Keywords

Property & Casualty InsuranceUnderwriting AutomationClaims IntelligenceFraud DetectionPricing AnalyticsRisk InsightsCustomer ServicingRegulatory ComplianceModel Risk ManagementResponsible AI

Tech Stack

Tools & technologies

AWSCloudETLGuidewireMicroservicesPMP

About the role

Key responsibilities & impact

Lead end-to-end delivery of Agentic AI and Generative AI initiatives from discovery and solutioning through deployment, adoption, and production support
Design and oversee autonomous and multi-agent solutions using large language models, retrieval-augmented generation, reasoning workflows, tool integration, and orchestration frameworks
Define AI transformation roadmaps, delivery plans, success metrics, governance standards, risk controls, and reusable accelerators
Guide responsible AI practices covering security, privacy, explainability, human oversight, hallucination controls, and regulatory compliance
Lead legacy-to-cloud data modernization, data migration, platform consolidation, and enterprise data transformation programs
Define and implement data governance, data quality, metadata management, master data management, data lineage, and lifecycle management capabilities
Oversee modernization of data lakes, data warehouses, lakehouse platforms, analytics ecosystems, and real-time data processing solutions
Drive DataOps practices, reusable ingestion and transformation frameworks, and standardized ETL/ELT delivery patterns
Provide technical oversight for AWS cloud-native data and AI platforms
Drive architecture decisions across data engineering, APIs, microservices, event-driven integration, containerization, infrastructure as code, and cloud security
Establish CI/CD, DevOps, MLOps, observability, reliability, performance, and cost-optimization practices
Manage cross-functional global teams of AI Engineers, Data Engineers, Data Scientists, Architects, Product Owners, Business Analysts, QA, DevOps, and domain SMEs
Own program planning, estimation, budgeting, staffing, delivery governance, dependency management, risk mitigation, and executive reporting
Facilitate business and technology workshops to identify high-value AI and data modernization opportunities
Communicate roadmaps, architecture decisions, delivery status, risks, and business outcomes to senior stakeholders and clients
Mentor teams and promote engineering excellence, delivery discipline, innovation, and reusable solution patterns
Partner with P&C insurance functions to identify AI-led transformation opportunities
Lead initiatives supporting underwriting automation, claims intelligence, fraud detection, pricing analytics, risk insights, and customer servicing
Align delivery with insurance data standards, governance expectations, privacy requirements, and regulatory controls

Requirements

What you’ll need

12+ years of experience across Data and Analytics, AI/ML, Cloud Transformation, Enterprise Architecture, or Digital Transformation
5+ years of experience leading large-scale data modernization, data management, cloud, AI, or analytics programs
Proven experience delivering enterprise AI, Generative AI, or Agentic AI solutions into production
Strong delivery leadership experience across globally distributed, cross-functional teams
Hands-on understanding of modern data architectures, data engineering, cloud-native design, APIs, security, DevOps, DataOps, and MLOps
Strong executive communication, client management, solutioning, estimation, governance, and risk-management skills
Property & Casualty (P&C) Insurance experience, including exposure to policy, claims, underwriting, actuarial, billing, risk, or insurance data ecosystems
Experience leading data migration, data management, or platform modernization programs within insurance organizations
Familiarity with Guidewire, Duck Creek, or other insurance core platforms
Experience with AI governance, model risk management, responsible AI, and regulated enterprise environments
PMP, SAFe, Scrum, AWS Solutions Architect, AWS Data Engineer, AWS Machine Learning, or relevant AI/data certifications
Business value realization and outcome measurement

Benefits

Comp & perks

Benefits information provided at https://www.exlservice.com/us-careers-and-benefits
Compensation may exceed the posted range for higher-cost zones such as California, New York, and New Jersey