Embedded AI Engineer for Enterprise Workflows

Careers at KKR; New York (NY); On-site; USD 180,000 - 200,000; Full time

Job summary

KKR is hiring a Forward Deployed Engineer to embed with investment teams, designing, building, and shipping production AI systems that improve decision making. You will work across private equity, credit, infrastructure, real estate, insurance, and capital markets to translate ambiguous business challenges into scalable technical solutions.

You will own architectures, data integration, deployment, and adoption, partnering with product, AI, data, security, and platform teams to create reusable

Qualifications

• Hands-on software engineering with production systems and end-to-end ownership.
• Experience building AI-enabled applications with large language models and tools.
• Strong data, API integration, and systems thinking skills.

Responsibilities

• Observe teams across KKR to map information flows and day-to-day realities.
• Identify high-value AI opportunities to remove bottlenecks and speed decisions.
• Translate business challenges into technical problem statements and delivery plans.
• Design, build, and ship production-grade AI applications, agents, integrations, and workflows.
• Create, test, and maintain reusable AI skills, tools, and workflow components for reuse across teams.
• Establish rigorous evaluations and metrics for accuracy, adoption and business impact.
• Move from discovery to production with strong emphasis on security, privacy, and reliability.

Skills

Python

TypeScript

LLMs

Data pipelines

APIs

Distributed systems

Security & privacy

Observability

Job description

KKR is hiring a Forward Deployed Engineer to embed with investment teams, designing, building, and shipping production AI systems that improve decision making. You will work across private equity, credit, infrastructure, real estate, insurance, and capital markets to translate ambiguous business challenges into scalable technical solutions.

You will own architectures, data integration, deployment, and adoption, partnering with product, AI, data, security, and platform teams to create reusable