Principal AI Solution Engineer

EPAM Systems; United States; A distancia; USD 180.000 - 240.000; Jornada completa

Descripción de la vacante

EPAM Systems is seeking a Principal AI Solution Engineer to join an engineering organization building a sovereign, multi-tenant agentic AI platform with Arabic and English support. Squads are small and decisions are made in the room, requiring credibility across applied AI, AI infrastructure and backend platform.

You will own architecture across three layers, lead GPU serving (vLLM, TGI or TensorRT-LLM), define RAG and agent infrastructure, and ensure robust, event-driven services with clear

Formación

• 5+ years of hands-on engineering experience across AI, infrastructure and backend platforms.
• At least 1 year of leadership experience.
• Proficiency in Python production stack (FastAPI, Pydantic, asyncio).
• Experience with production RAG end‑to‑end: ingestion, vector search, reranking and grounding evaluation.

Responsabilidades

• Define architecture spanning squads; document decisions and defend them.
• Build and tune GPU-based serving (vLLM, TGI or TensorRT-LLM) for latency, throughput and cost per token.
• Own the reference RAG and agent architecture used by other teams.
• Define service boundaries, API contracts, event-driven infrastructure and the SLO work that prevents incidents.
• Develop offline and online evaluation and regression detection to evolve models safely.

Conocimientos

Leadership

Distributed systems

Architectural decision making

English communication

AI platform experience

Herramientas

Python

FastAPI

Pydantic

asyncio

vLLM

TGI

TensorRT-LLM

LangGraph

LangChain

OpenAI Agent SDK

Kubernetes on Azure

PostgreSQL

CLAUDE.md

Descripción del empleo

We are seeking a Principal AI Solution Engineer to join an engineering organization building a sovereign, multi-tenant agentic AI platform, along with the applied products on top of it. Everything ships under strict data residency constraints and operates in both Arabic and English. Squads are small — three senior engineers — and decisions are made in the room. You will work across three layers and need to be credible in all of them: applied AI, AI infrastructure, and the backend platform.

Responsibilities

• Set architecture for systems that span squads; write the decision down and defend it
• Build and tune GPU-based serving — vLLM, TGI or TensorRT-LLM — for latency, throughput and a cost per token you can justify
• Own the reference RAG and agent architecture other teams build against
• Define service boundaries, API contracts, event-driven infrastructure and the SLO work that prevents incidents rather than answering them
• Develop offline and online evaluation and regression detection, so models, prompts and retrieval can change without flying blind

Requirements

• 5+ years of hands‑on engineering experience with shipped production systems spanning applied AI, AI infrastructure and backend platforms
• At least 1 year of relevant leadership experience
• Expertise in Python and its production ecosystem, including FastAPI, Pydantic and asyncio
• Proficiency in production RAG end‑to‑end: ingestion, vector search, reranking and grounding evaluation
• Background in agent orchestration frameworks such as LangGraph, LangChain, OpenAI Agent SDK or Microsoft Agent Framework
• Competency in distributed systems, including idempotency, back‑pressure and retry semantics, with strong event‑driven architecture skills
• Knowledge of PostgreSQL at scale, along with GPU inference and serving using vLLM, TGI or TensorRT-LLM
• Familiarity with Kubernetes on Azure
• Skills in at least one infrastructure language: Go, Rust, Java or Kotlin
• Capability to use agentic coding tooling as a daily workflow, including project setup with CLAUDE.md, skills and agent configuration
• Excellent command of written and spoken English (B2+ level)

Nice to have

• Nice to have Showcase of pgvector or Qdrant at production scale
• Experience with Arabic-language, voice or conversational AI
• Background in AI or mission‑critical delivery in regulated environments such as government, defence or financial services
• Familiarity with Azure sovereign cloud, Entra ID and Azure OpenAI
• Understanding of Langfuse, Grafana, Prometheus and Terraform