Private Equity Engineering Lead

Careers at KKR•New York, NY

1d•$170,000 - $190,000

About The Position

KKR’s Investment Technology group builds and operates systems across the investment lifecycle. The group develops shared, data-driven platforms for Private Equity, Credit, Real Estate, Infrastructure and Capital Markets, replacing fragmented legacy tools with integrated solutions. The Vice President, Engineering Lead will own the end-to-end engineering of a new platform for the Private Equity middle and back office, including its capital-activity and accounting engine, underlying data model, integrations and migration away from legacy systems. This is a build role rather than an implementation of a purchased product. The role leads a small, senior team of three to four engineers as a player-coach, spending approximately 40–60% of the time designing, writing and reviewing code. Delivery is closely coordinated with other groups across the firm through shared roadmaps and trade-off decisions. The platform’s scope includes capital calls and distributions; management fees, fund accounting and partnership allocations; co-investment tracking; funding-instruction generation for Treasury Technology; and reconciliation and data-quality automation. The role works with business and technology partners to reduce cycle times and manual effort, establish controls and engineering standards, and report progress against measurable goals. The expected annual base salary range for this New York-based position is $170,000–$190,000. Employees may be eligible for a discretionary bonus based on factors including individual and team performance.

Requirements

At least 10 years of professional software engineering experience, including at least 3 years leading an engineering team, mentoring, planning and managing performance.
Track record of building complex, multi-component systems from the ground up, including transactional or calculation-heavy systems where accuracy and auditability matter, and ability to explain how correctness was established.
Current hands-on proficiency in Python and SQL, building production systems and data pipelines on AWS; willingness to spend 40–60% of time coding and reviewing.
Sound architectural judgment, including API and event-driven integration, clear ownership boundaries between data owned and consumed, and examples of decisions made early versus deferred.
Experience leading at least one legacy-system migration through parallel run, cutover and actual decommissioning.
Experience delivering work dependent on multiple teams, including non-engineering partners such as operations or finance, external vendors, and at least one project involving a core platform owned by another group.
Ability to explain technical trade-offs in plain terms to controllers or operations leads; collaborative, low-ego approach and strong ownership of outcomes and system health.
Bachelor’s degree in computer science, engineering or a related field preferred, or equivalent practical experience.

Nice To Haves

Familiarity with private-markets fund accounting and operations, including capital calls and distributions, waterfalls and carried interest, partnership allocations, NAV, management fees and ABOR systems.
Exposure to fund administrator data feeds, investor reporting (ILPA templates), valuation (ASC 820 / IPEV), or treasury and bank connectivity.
Experience with Snowflake, PySpark, workflow orchestration such as Kestra or Argo, and reference-data or bitemporal modeling.
Background in ledgers and payments, securities operations, insurance policy administration, or finance and ERP system builds, or comparable domains where correctness is non-negotiable.
Practical experience applying LLMs to document extraction or exception handling, with evaluation and controls.

Responsibilities

Lead, mentor and develop a team of senior software and data engineers; set goals and operating rhythms, provide feedback, and develop engineering and domain expertise.
Own the architecture and build of the canonical data model, calculation and capital-activity engine, and integration layer.
Write production code on critical-path components, author and chair design reviews, and review calculation, reconciliation and controls logic.
Lead migration from legacy systems, including data migration, parallel run, cutover, rollback planning and decommissioning.
Coordinate partner teams through a shared roadmap, dependency board and joint operating rhythm, aligning stakeholders before decisions are needed.
Partner with fund accounting, fund operations, finance, treasury, valuation, investor reporting, tax and compliance to reduce cycle times and manual effort against measured baselines.
Build controls into the platform and set engineering standards for CI/CD, testing, observability and incident management.
Apply AI selectively to document extraction and reconciliation-exception triage, using evaluation sets and human approval where it measurably helps.
Report progress to technology and business leadership against a metrics scorecard.