Engagement Lead

ABOUT THE ROLE

We are seeking an experienced Agentic Data Delivery Lead to own the end-to-end execution of complex AI and data programs, from project kick-off through sustained production operations. This is a hands-on technical leadership role requiring a strong foundation across AI/ML, agentic AI, data engineering, cloud data platforms, and enterprise delivery, along with client-facing accountability and domain exposure across insurance.

You will lead cross-functional teams of data engineers, AI/ML engineers, agentic AI specialists, cloud architects, and business analysts. You will manage stakeholder relationships and act as the technical conscience of the program, ensuring that agentic data solutions are scalable, secure, governed, delivered on time, and aligned to measurable business outcomes.

WHAT YOU'LL DO

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 – Agentic AI & Data

• Provide hands-on technical oversight of data platform builds: ingestion pipelines, transformation layers, semantic models, and analytics APIs
• Guide the design and deployment of production-grade agentic AI solutions, including agent orchestration, multi-agent workflows, RAG/GraphRAG, tool and API integration, prompt and context engineering, agent memory, human-in-the-loop controls, evaluation, observability, governance, and guardrails
• Lead integration of AI agents with enterprise data platforms, APIs, workflow systems, knowledge bases, and business applications while maintaining security, privacy, auditability, and access controls
• Define evaluation and production-readiness standards covering task success, groundedness, hallucination and safety testing, tool-call accuracy, latency, scalability, token usage, cost, fallback paths, and incident management
• Drive reusable agentic accelerators, reference architectures, and delivery playbooks across AI and data programs
• 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

WHAT YOU BRING

Required

• 15+ years in data engineering, AI/ML, or analytics — with at least 7 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), data Lakehouse architectures(Databricks, Delta Lake), and orchestration tools (Airflow, dbt)
• Strong knowledge of agentic AI architectures, including LLM orchestration frameworks, RAG and GraphRAG pipelines, multi-agent systems, planning and reasoning patterns, tool/function calling, agent memory, evaluation frameworks, observability, responsible AI, and enterprise deployment patterns
• Ability to balance solution quality, autonomy, human oversight, regulatory risk, latency, scalability, and cost when designing agentic workflows
• 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 exposure across P&C, Life & Annuities, underwriting, claims, policy administration, distribution, servicing, or regulatory reporting
• Data migration and data modernization project experience: legacy system decommissions, cloud lift-and-shift, or greenfield platform builds
• Ability to work with domain SMEs, product owners, architects, and compliance stakeholders to define safe, explainable, and measurable AI-enabled workflows
• Certifications: AWS /Azure Data, Databricks, Snowflake, PMP/SAFe, or equivalent

Base Compensation Range: $160,000- $200,000k

The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.