Lead AI Agentic Developer

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

Benefits offered by this job

Healthcare benefits

Paid time off & sick leave

Upskilling & certifications

Global career opportunities

Volunteer opportunities

Job summary

EPAM Systems, Inc. seeks a Lead AI Agentic Developer to lead AI-powered engineering initiatives across Python/FastAPI, React/TypeScript, and Google Cloud Vertex AI. You will own GenAI systems end-to-end, including orchestration, observability, and cost controls, while collaborating with cross-functional teams.

You will apply prompt-engineering techniques, leverage AI coding assistants, and drive scalable, production-ready AI solutions with strong operational readiness and business alignment.

Qualifications

• 5+ years of software development with hands-on generative AI experience.
• Experience with AI coding assistants (Claude Code, GitHub Copilot).
• Strong knowledge of LLM orchestration, RAG, multi-agent systems, and tool calling.

Responsibilities

• Design, build, deploy, and support AI-powered applications across Python/FastAPI and React/TypeScript.
• Own GenAI systems end-to-end, including cost optimization and observability.
• Implement LLM orchestration, prompt engineering, retrieval-augmented generation, and multi-agent workflows.

Skills

GenAI development

Python

FastAPI

React

TypeScript

LLM observability

Prompt engineering

RAG architectures

Docker

Kubernetes

Tools

LangFuse

LangSmith

Grafana

Dynatrace

Splunk

GitHub Copilot

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.ResponsibilitiesDesign, 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 standardsOwn GenAI systems end to end, covering architecture choices, feature delivery, operational readiness, production support, and cost optimizationApply AI-augmented engineering workflows and collaborate effectively with AI coding assistants such as Claude Code and GitHub Copilot to speed delivery and improve code qualityCollaborate with solution engineers, architects, and product teams to produce technical design specifications and confirm alignment with architectural standards, non-functional requirements, and business needsImplement LLM orchestration approaches including prompt engineering, retrieval-augmented generation (RAG), multi-agent workflows, and structured-output generationCreate and maintain observability pipelines for AI platforms, including trace analysis, token-usage tracking, cost monitoring, and quality metricsProvide technical leadership and mentorship to help teammates grow in agentic development practices, prompt-engineering techniques, and AI-tool integrationEvaluate cross-platform trade-offs across backend technologies, frontend technologies, and AI services to maintain architectural consistency and identify optimization opportunitiesTroubleshoot defects, perform root-cause analysis, and code, test, and deliver full-stack enhancementsCommunicate risks, blockers, and schedule impacts early to ensure on-time delivery of AI initiatives and drive resolution to protect commitmentsCoordinate multiple deliverables across services and platforms, handle operational requests, and resolve production issues efficientlyUse observability and monitoring tools including LangFuse, Grafana, Dynatrace, and Splunk to review dashboards, investigate anomalies, monitor AI-model performance, and track cost metricsRequirementsProven 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 WindsurfDeep expertise in generative AI application development, GenAI design patterns, and GenAI cloud platforms including Google Cloud Vertex AI, Gemini, Anthropic Claude, and OpenAIHands-on experience with LLM observability and tracing using Langfuse, LangSmith, or similar platformsStrong skills in prompt-engineering methods such as chain-of-thought prompting, few-shot learning, and structured outputsSolid understanding of LLM orchestration, RAG architectures, multi-agent systems, tool calling, and agent evaluationAdvanced proficiency in Python, FastAPI, asynchronous programming, Pydantic, and SQLAlchemy ORMStrong background with MySQL and PostgreSQL, including query optimization and Alembic migrationsPractical 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 orchestrationHands-on frontend skills with React, TypeScript, Zustand state management, and Material UI (MUI)Working knowledge of data-visualization libraries including Recharts and D3.jsStrong experience with Google Cloud Platform, including Vertex AI, Cloud Run, BigQuery, Cloud Storage, and IAM, plus Git, CI/CD, GitHub Actions, and ArgoCDEnglish proficiency at B2 level (Upper-Intermediate) or higherWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedIn