Job Description: 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
Responsibilities: 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
