Product Delivery Lead - Insurance Data

Careers at KKR•Boston, MA

About The Position

KKR is seeking a Tech Product & Delivery Lead for Insurance Data and AI to own the end-to-end strategy, roadmap, and delivery of technology solutions that power KKR's insurance data and AI capabilities. This includes policy, investments, and actuarial data platform architecture, data governance and quality, enterprise insurance data catalog, machine learning infrastructure, generative AI tooling, and firmwide insurance analytics enablement. The role involves partnering closely with the Data and AI leadership team and engineering teams to shape the multi-year vision, build and lead a team of product managers and delivery leads, and drive complex programs. This senior role acts as a bridge between Insurance Data and AI stakeholders and engineering, ensuring business priorities are understood to drive prioritization, modernization, and responsible-AI-enabled transformation of how KKR's insurance platform companies collect, govern, and derive value from data globally.

Requirements

12+ years of experience in system implementations, product management, technology delivery, or transformation roles, with meaningful time spent leading Insurance Data and AI technology programs, ideally within life insurance, reinsurance, or large insurance enterprise environments.
Proven track record of building and leading product and delivery teams, and of personally delivering enterprise insurance data and AI technology programs at scale across multiple geographies.
Experience partnering with engineering teams, vendors, and systems integrators, and leading complex, cross-functional initiatives in a matrixed environment with executive stakeholders.
Deep understanding of the end-to-end insurance data-to-insight lifecycle and the operating model of a modern insurance data and AI function – including policy, investments, and actuarial data platform architecture, data governance and quality, MLOps, generative AI enablement, and analytics / BI.
Hands-on familiarity with leading Insurance Data and AI technology platforms across the stack – for example, Snowflake, Databricks, or Microsoft Fabric for data platform / lakehouse; Collibra or Alation for data catalog / governance; MLflow, SageMaker, or Vertex AI for MLOps; Azure OpenAI or Bedrock for generative AI; and Power BI, Tableau, or Sigma for analytics / BI.
Knowledge of data privacy regulation (e.g., GDPR, CCPA), model risk management, NAIC / state insurance regulatory expectations on data and AI, and emerging AI governance frameworks and their implications on insurance data and AI technology and architecture.
Technical fluency with enterprise insurance data and AI/ML platforms, identity and access management, data governance, workflow automation, and emerging AI/ML tools applied to analytics use cases.
Experience designing and implementing workflow automation platforms, integration architectures (APIs, event streams, iPaaS), and insurance-specific data models and semantic layers across multiple best-of-breed vendor systems.
Familiarity with cloud architecture, modern data management, and analytics tools (e.g., Python, SQL, Power BI, Sigma, Tableau, or equivalent) and with building a governed data and analytics layer on top of operational underwriting, investments, and actuarial systems.
Understanding of enterprise DevOps, CI/CD practices, and modern SDLC frameworks, and how they apply in a configuration-heavy SaaS insurance data / AI platform environment.
Ability to design and communicate a long-term vision for the Insurance Data and AI technology stack while delivering incremental business value each cycle.
Strategic thinking with the ability to align product and delivery initiatives with broader enterprise technology vision, the firm's insurance data strategy, and business objectives.
Strong ability to engage, influence, and align diverse stakeholders across Data Governance, Actuarial, Legal, Compliance, and Technology functions globally.
Excellent articulation and executive presence to engage Data Ops, Insurance Data and AI leadership, and Technology leadership, as well as to coach and mentor product and delivery teams.
Ability to build consensus and drive execution in a complex, fast-moving, and highly confidential environment.
Skilled at prioritization, governance, and managing delivery timelines across a multi-workstream portfolio without compromising quality.
Strong program management capabilities to drive execution discipline across multiple technology teams, vendors, and concurrent insurance data and AI delivery cycles.
Strong skills in problem-solving, data analysis, and translating insights into product and delivery decisions.
Ability to balance technical feasibility, vendor capabilities, business needs, and end-user experience.
Able to drive adoption of new solutions and embed them into business and insurance data processes, including the change management required for global Insurance Data and AI rollouts.
Passion for innovation and for driving transformational change in how the firm's insurance platform companies use data and AI – with empathy for the user experience.
Excellent written and verbal communication skills with the ability to translate complex technical concepts for non-technical audiences, including senior insurance data and business leaders.
Strong collaboration skills to work effectively across global, cross-functional teams and to lead distributed product and delivery teams.
Bachelor's degree in Computer Science, Data Science, Statistics, or Actuarial Science.

Nice To Haves

MBA or advanced degree preferred.

Responsibilities

Define and own the multi-year technology strategy and roadmap for the end-to-end Insurance Data and AI technology stack, ensuring alignment with the firm's insurance data strategy and business priorities.
Drive prioritization and governance of the Insurance Data and AI technology portfolio, balancing near-term operational needs with long-term platform modernization.
Stay current on emerging trends across insurance data platforms, MLOps, LLM / generative AI tooling, and actuarial and investments data governance technology, bringing innovation into the roadmap.
Partner with Data Operations, Actuarial, Underwriting Analytics, Model Risk Management, and business-unit data stewards to understand business requirements and translate them into scalable technology solutions.
Collaborate closely with engineering leads to design scalable, secure, and efficient solutions supporting the full insurance data-to-insight lifecycle.
Serve as the senior technology partner to the Insurance Data and AI function, facilitating cross-functional collaboration and building deep partnerships with insurance business leaders globally.
Lead a team of product managers and delivery leads, setting standards for discovery, requirements management, delivery cadence, and adoption.
Oversee end-to-end product lifecycle for all Insurance Data and AI platforms, including requirements gathering, vendor selection, solution design, configuration, testing, rollout, change management, adoption, and continuous improvement.
Drive the development and implementation of platforms supporting the full insurance data-to-insight lifecycle.
Ensure Insurance Data and AI technology solutions deliver an integrated, modern data and analytics experience with workflow automation, self-service access, and real-time insights.
Own delivery accountability for the portfolio, including budget, vendor relationships, SOWs, milestones, risks, and stakeholder communication.
Champion the modernization and automation of the Insurance Data and AI technology stack, including cloud-native architecture and the application of advanced analytics and generative AI.
Evaluate and integrate best-of-breed Insurance Data and AI technology solutions as needed to enhance capabilities.
Lead the responsible adoption of AI-enabled capabilities across the insurance data lifecycle with appropriate governance and human oversight.
Drive adoption of new solutions and embed them into the day-to-day workflows of users, ensuring measurable impact and a best-in-class user experience.
Ensure all Insurance Data and AI technology platforms meet global regulatory expectations, including data privacy, model risk management, and emerging AI governance regulations.
Partner with Legal, Compliance, Information Security, and Model Risk Management to align solutions with enterprise risk management frameworks.
Implement controls, access models, and risk mitigation protocols aligned with enterprise technology policies.
Monitor adoption and performance of deployed Insurance Data and AI platforms, leveraging feedback for continuous enhancements.
Lead continuous improvement initiatives to enhance system performance, user experience, process efficiency, and business value delivery.
Define, measure, and report on key product and delivery metrics to leadership.