Lead AI Agentic Developer

EPAM Systems Inc; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

EPAM Systems is seeking a Lead AI Agentic Developer to drive AI-powered engineering initiatives spanning backend Python/FastAPI, frontend React/TypeScript, and Google Vertex AI.

You will own GenAI systems end-to-end, ensuring observability, cost controls, and collaboration with AI coding assistants to accelerate delivery. The role requires a strong foundation in software development and cloud tooling.

Qualifications

• 5+ years of software development experience with hands-on GenAI and agentic development including AI coding assistants like Claude Code and GitHub Copilot
• Deep expertise in GenAI design patterns and GenAI cloud platforms including Vertex AI
• Hands-on experience with LLM observability and tracing using LangFuse, LangSmith, or similar platforms
• Strong skills in prompt-engineering methods and structured outputs
• Solid understanding of LLM orchestration, RAG, multi-agent systems, tool calling, and agent evaluation
• Proficiency in Python, FastAPI, asynchronous programming, Pydantic, and SQLAlchemy
• Experience with Docker, Kubernetes, and modern CI/CD
• Knowledge of authentication/authorization patterns (OAuth 2.0, JWT, RBAC)
• Frontend experience with React/TypeScript and data-visualization basics

Responsibilities

• Design, build, deploy, and support AI-powered apps using Python/FastAPI backends, React/TypeScript frontends, and Vertex AI
• Own GenAI systems end-to-end including architecture choices, feature delivery, operational readiness, and cost optimization
• Collaborate with AI coding assistants to speed delivery and improve code quality
• Create technical design specifications aligned with standards and business needs
• Implement LLM orchestration, RAG, multi-agent workflows, and structured-output generation
• Create observability pipelines with trace analysis, token usage, and cost metrics
• Provide technical leadership and mentorship in agentic development and AI-tool integration
• Evaluate cross-platform trade-offs for architecture consistency and optimization
• Troubleshoot defects, perform root-cause analysis, and deliver full-stack enhancements
• Communicate risks and blockers early to protect commitments
• Coordinate multiple deliverables and resolve production issues efficiently
• Monitor dashboards and AI-model performance using LangFuse, Grafana, Dynatrace, Splunk

Skills

Generative AI

Agentic development

Python

FastAPI

React

TypeScript

LLM observability

Docker

Kubernetes

SQLAlchemy ORM

OAuth 2.0

JWT

RBAC

Vertex AI

BigQuery

GitHub Actions

ArgoCD

LangFuse

Grafana

Dynatrace

Splunk

CI/CD

Tools

LangSmith

Grafana

Dynatrace

Splunk

Vertex AI

BigQuery

Job description

We are building a Lead AI Agentic Developer role to lead AI-powered engineering initiatives that elevate the retail experience through generative AI. You will own agentic and RAG solutions end-to-end across Python/FastAPI, React/TypeScript, and Google Cloud Vertex AI, with strong observability and cost controls.

Responsibilities

• Design, build, deploy, and support AI-powered applications using Python/FastAPI backends, React/TypeScript frontends, and Google Cloud Vertex AI while following best practices and quality standards
• Own GenAI systems end to end, covering architecture choices, feature delivery, operational readiness, production support, and cost optimization
• Apply AI-augmented engineering workflows and collaborate effectively with AI coding assistants such as Claude Code and GitHub Copilot to speed delivery and improve code quality
• Collaborate with solution engineers, architects, and product teams to produce technical design specifications and confirm alignment with architectural standards, non-functional requirements, and business needs
• Implement LLM orchestration approaches including prompt engineering, retrieval-augmented generation (RAG), multi-agent workflows, and structured-output generation
• Create and maintain observability pipelines for AI platforms, including trace analysis, token-usage tracking, cost monitoring, and quality metrics
• Provide technical leadership and mentorship to help teammates grow in agentic development practices, prompt-engineering techniques, and AI-tool integration
• Evaluate cross-platform trade-offs across backend technologies, frontend technologies, and AI services to maintain architectural consistency and identify optimization opportunities
• Troubleshoot defects, perform root-cause analysis, and code, test, and deliver full-stack enhancements
• Communicate risks, blockers, and schedule impacts early to ensure on-time delivery of AI initiatives and drive resolution to protect commitments
• Coordinate multiple deliverables across services and platforms, handle operational requests, and resolve production issues efficiently
• Use observability and monitoring tools including LangFuse, Grafana, Dynatrace, and Splunk to review dashboards, investigate anomalies, monitor AI-model performance, and track cost metrics

Requirements

• Proven background of 5+ years in software development, including hands-on generative AI and agentic development with AI coding assistants such as Claude Code, GitHub Copilot, Cursor, and Windsurf
• Deep expertise in generative AI application development, GenAI design patterns, and GenAI cloud platforms including Google Cloud Vertex AI, Gemini, Anthropic Claude, and OpenAI
• Hands-on experience with LLM observability and tracing using Langfuse, LangSmith, or similar platforms
• Strong skills in prompt-engineering methods such as chain-of-thought prompting, few-shot learning, and structured outputs
• Solid understanding of LLM orchestration, RAG architectures, multi-agent systems, tool calling, and agent evaluation
• Advanced proficiency in Python, FastAPI, asynchronous programming, Pydantic, and SQLAlchemy ORM
• Strong background with MySQL and PostgreSQL, including query optimization and Alembic migrations
• Practical knowledge of authentication and authorization patterns including OAuth 2.0, Okta, JWT, and role-based access control (RBAC)
• Proven experience with Docker, Docker Compose, Kubernetes, and container orchestration
• Hands-on frontend skills with React, TypeScript, Zustand state management, and Material UI (MUI)
• Working knowledge of data-visualization libraries including Recharts and D3.js
• Strong experience with Google Cloud Platform, including Vertex AI, Cloud Run, BigQuery, Cloud Storage, and IAM, plus Git, CI/CD, GitHub Actions, and ArgoCD
• English proficiency at B2 level (Upper-Intermediate) or higher