Embedded AI Engineer for Enterprise Workflows

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

Benefits offered by this job

Discretionary bonus

Job summary

KKR is hiring a Forward Deployed Engineer in New York to embed with investment teams and build production AI systems that streamline workflows. You will own end‑to‑end delivery from architecture to deployment, collaborating with product, data, security, and platform teams.

The role emphasizes transforming ambiguous business challenges into concrete technical solutions, shipping reusable platform components, and driving adoption across business units within a regulated enterprise environment.

Qualifications

• Hands-on software engineering for production AI systems.
• Proficiency in Python or TypeScript with APIs and cloud experience.
• Experience building AI-enabled applications and evaluating behavior.
• Data pipelines, databases, and retrieval systems handling unstructured content.
• Experience with enterprise data and cross-team collaboration.
• Ability to work with senior business stakeholders and translate needs into technical solutions.

Responsibilities

• Observe business workflows across teams to understand information flows and bottlenecks.
• Identify opportunities where AI reduces manual tasks and improves decision quality.
• Define architectures, delivery plans, and production-grade AI applications.
• Build and ship AI agents, integrations, and workflow automations.
• Design data pipelines and interfaces to enable AI usability.
• Create reusable skills, tools, and framework components across teams.
• Establish metrics for accuracy, reliability, adoption and impact.

Skills

Python

TypeScript

LLM applications

Data pipelines

APIs

Cloud platforms

Distributed systems

Security and privacy

Observability

Collaboration with stakeholders

Job description

KKR is hiring a Forward Deployed Engineer in New York to embed with investment teams and build production AI systems that streamline workflows. You will own end‑to‑end delivery from architecture to deployment, collaborating with product, data, security, and platform teams.

The role emphasizes transforming ambiguous business challenges into concrete technical solutions, shipping reusable platform components, and driving adoption across business units within a regulated enterprise environment.