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Kroll

Global risk management and investigations consulting

Lead Engineer - AI-Native Product Development

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • 6–10+ years of full-stack software engineering experience.
  • Proven experience building and shipping production systems.
  • Deep familiarity with modern frontend and backend web frameworks.
  • Strong architectural design capability.
  • Demonstrated proficiency with agentic coding tools such as Claude Code or equivalent.
  • Experience orchestrating multi-agent workflows for development tasks.
  • Comfort designing systems where AI is embedded into the build process.
  • Ability to rigorously evaluate, validate, and supervise AI-generated code.
  • Experience with frontend frameworks such as React, Next.js, or similar.
  • Backend development experience with Node, Python, or similar.
  • API design and integration capability.
  • Cloud-native architecture knowledge.
  • Experience with automated testing frameworks and CI/CD.

Responsibilities

  • Own full-stack development of AI-enabled internal products.
  • Translate workflow requirements into scalable application architectures.
  • Deliver production-grade systems aligned with enterprise security and governance requirements.
  • Maintain accountability for performance, reliability, and maintainability.
  • Design and orchestrate groups of coding agents to generate modular code components, refactor and optimize legacy code, write and execute test suites, and generate documentation and developer artifacts.
  • Use tools such as Claude Code and related agentic frameworks to accelerate development cycles.
  • Build repeatable development pipelines combining human oversight with AI execution.
  • Architect guardrails for deterministic outputs, version control integrity, and testing validation.
  • Apply AI across the software development lifecycle, including UX wireframing and rapid interface prototyping, schema design and backend service scaffolding, automated test generation and regression testing, performance tuning and debugging support, and CI/CD pipeline enhancement.
  • Apply AI to product design, quality assurance, and documentation in addition to coding.
  • Partner with Product and AI Transformation leaders to prioritize high-impact workflow tools.
  • Work directly with service line stakeholders to understand domain constraints and regulatory considerations.
  • Collaborate with data and machine learning engineers when integrating models or AI services.
  • Ensure defensibility, security, and compliance alignment in all builds.

About the Company

Kroll

Global risk management and investigations consulting

Preparing summary

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
New York City, New York
Founded
1932

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