Lead AI Engineer, Insurance Automation Innovator

EPAM Systems; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Learning opportunities

Global career opportunities

Job summary

EPAM Systems, Inc. seeks a Lead AI Engineer to advance the insurance sector using agent-based AI technology.

You will develop smart automation products that handle sophisticated insurance activities, giving brokers greater capacity for advisory work and stronger client engagement. Responsibilities include examining broking activities to identify opportunities, delivering AI platforms with LLMs, RAG, and multi-agent designs, and guiding the end-to-end lifecycle from discovery to production and

Qualifications

• 5+ years in software development or AI-related roles.
• Experience bringing AI initiatives from exploration to live production.
• Strong Python and TypeScript coding and system design skills.
• Familiarity with LLMs, RAG, document understanding and data extraction.

Responsibilities

• Examine broking activities to identify automation opportunities.
• Build and launch AI platforms for insurance workflows and processes.
• Deliver AI-driven solutions using LLMs, RAG, and multi-agent designs.
• Lead discovery, prototyping, release, and measurement of AI offerings.
• Establish validation, system metrics, production visibility, and safety gates.
• Coach teams and promote repeatable, secure AI engineering practices.

Skills

Python

TypeScript

Machine Learning

LLM technologies

CI/CD automation

Communication

Tools

Docker

Kubernetes

Terraform

Observability tools

Job description

EPAM Systems, Inc. seeks a Lead AI Engineer to advance the insurance sector using agent-based AI technology.

You will develop smart automation products that handle sophisticated insurance activities, giving brokers greater capacity for advisory work and stronger client engagement. Responsibilities include examining broking activities to identify opportunities, delivering AI platforms with LLMs, RAG, and multi-agent designs, and guiding the end-to-end lifecycle from discovery to production and