Delivery Lead - AI & Data

Delivery Lead – AI & Data End-to-End Delivery Ownership | Agentic Data Programs | Enterprose Data Modernization | Insurance 📍 India (Gurgaon/Delhi/NCR )   |    🏢 External   |   📅 Full-Time

We are seeking an experienced Delivery Lead to own the end-to-end execution of complex AI & Data programs — from project kick-off to sustained production operations. This is a hands-on technical leadership role with strong client-facing accountability: you will be the single point of ownership for delivery outcomes within signed scope while actively mining for expansion opportunities through exceptional execution.

You will lead cross-functional delivery teams, manage stakeholder relationships, and act as the technical conscience of the program ensuring that agentic data solutions are built right, on time, and at value.

Delivery Ownership & Program Governance

• Own end-to-end delivery accountability for one or more concurrent AI & Data programs against signed scope, budget, and timeline
• Establish and drive program governance: sprint cadences, steering committees, risk registers, change control, and delivery dashboards
• Lead technical delivery teams of data engineers, AI/ML engineers, cloud architects, BAs— typically 10–30 FTEs
• Proactively identify and mitigate risks, dependencies, and blockers before they impact client commitments
• Manage scope, effort estimation, and resource allocation across the program lifecycle

Technical Leadership – Data & Agentic AI

• Provide hands-on technical oversight of data platform builds: ingestion pipelines, transformation layers, semantic models, and analytics APIs
• Guide the design and deployment of agentic AI solutions: agent orchestration, tool integrations, prompt engineering governance, and guardrails
• Conduct architecture reviews, technical spike planning, and code/quality gates across delivery workstreams
• Champion engineering best practices — CI/CD, data observability, lineage, testing frameworks — across the delivery team
• Drive data migration and modernization programs: schema mapping, ETL/ELT, cutover planning, reconciliation, and go-live

Client Engagement & Account Mining

• Serve as the primary day-to-day client interface for delivery: building trusted relationships with client program managers, architects, and domain owners
• Conduct regular client steering reviews, translating delivery metrics into business-impact narratives
• Identify and surface expansion opportunities (new workstreams, adjacent use cases, capacity growth) through quality delivery

Required

• 10+ years in data engineering, AI/ML, or analytics — with at least 4 years in a delivery leadership or program management role
• Proven track record delivering complex, multi-workstream AI & Data programs in a services/consulting environment
• Hands-on technical expertise in modern data stacks: cloud data warehouses (Snowflake, Databricks, Redshift), data Lakehouse architectures(Databricks, Delta Lake), and orchestration tools (Airflow, dbt)
• Working knowledge of agentic AI architectures: LLM orchestration frameworks, RAG pipelines, multi-agent systems, and enterprise deployment patterns
• Strong client-facing communication — ability to present delivery progress, risks, and trade-offs to senior business and technology stakeholders
• Experience managing distributed delivery teams (India + offshore/onshore model)
• Bachelor's or Master's degree in Computer Science, Engineering, or related field

Preferred / Nice to Have

• Insurance domain experience: P&C, Life & Annuities, Claims, Policy, or Underwriting data programs
• Data migration and data modernization project experience: legacy system decommissions, cloud lift-and-shift, or greenfield platform builds
• Familiarity with insurance data frameworks, regulatory reporting, and ACORD standards
• Certifications: AWS /Azure Data, Databricks, Snowflake, PMP/SAFe, or equivalent

Technical Anchor Skills:

  Agentic AI / LLM Orchestration 

  Data Platform Engineering (Snowflake / Databricks / BigQuery) 

  dbt / Airflow / Spark 

  Data Migration & Modernization 

  CI/CD & Data Observability 

Leadership & Delivery Skills:

  Program Governance & Risk Management 

  Client Stakeholder Management 

  Distributed Team Leadership 

  Account Mining Through Delivery 

  Insurance Domain (Plus) 

• Lead programs that ship real AI agents into production — not POCs that get shelved
• High-visibility role with direct influence on client outcomes and account growth
• Collaborate with US-based engagement leads and global architects on industry-leading solutions
• Strong career path into architecture, practice leadership, or account management

Required

• 10+ years in data engineering, AI/ML, or analytics — with at least 4 years in a delivery leadership or program management role
• Proven track record delivering complex, multi-workstream AI & Data programs in a services/consulting environment
• Hands-on technical expertise in modern data stacks: cloud data warehouses (Snowflake, Databricks, Redshift), data Lakehouse architectures(Databricks, Delta Lake), and orchestration tools (Airflow, dbt)
• Working knowledge of agentic AI architectures: LLM orchestration frameworks, RAG pipelines, multi-agent systems, and enterprise deployment patterns
• Strong client-facing communication — ability to present delivery progress, risks, and trade-offs to senior business and technology stakeholders
• Experience managing distributed delivery teams (India + offshore/onshore model)
• Bachelor's or Master's degree in Computer Science, Engineering, or related field

Preferred / Nice to Have

• Insurance domain experience: P&C, Life & Annuities, Claims, Policy, or Underwriting data programs
• Data migration and data modernization project experience: legacy system decommissions, cloud lift-and-shift, or greenfield platform builds
• Familiarity with insurance data frameworks, regulatory reporting, and ACORD standards
• Certifications: AWS /Azure Data, Databricks, Snowflake, PMP/SAFe, or equivalent

Delivery Ownership & Program Governance

• Own end-to-end delivery accountability for one or more concurrent AI & Data programs against signed scope, budget, and timeline
• Establish and drive program governance: sprint cadences, steering committees, risk registers, change control, and delivery dashboards
• Lead technical delivery teams of data engineers, AI/ML engineers, cloud architects, BAs— typically 10–30 FTEs
• Proactively identify and mitigate risks, dependencies, and blockers before they impact client commitments
• Manage scope, effort estimation, and resource allocation across the program lifecycle

Technical Leadership – Data & Agentic AI

• Provide hands-on technical oversight of data platform builds: ingestion pipelines, transformation layers, semantic models, and analytics APIs
• Guide the design and deployment of agentic AI solutions: agent orchestration, tool integrations, prompt engineering governance, and guardrails
• Conduct architecture reviews, technical spike planning, and code/quality gates across delivery workstreams
• Champion engineering best practices — CI/CD, data observability, lineage, testing frameworks — across the delivery team
• Drive data migration and modernization programs: schema mapping, ETL/ELT, cutover planning, reconciliation, and go-live

Client Engagement & Account Mining

• Serve as the primary day-to-day client interface for delivery: building trusted relationships with client program managers, architects, and domain owners
• Conduct regular client steering reviews, translating delivery metrics into business-impact narratives
• Identify and surface expansion opportunities (new workstreams, adjacent use cases, capacity growth) through quality delivery