Senior Python AI Solution Engineer

EPAM Systems; Argentina; On-site; ARS 106,112,000 - 166,748,000; Full time

Benefits offered by this job

Healthcare benefits

Employee financial programs

Paid time off and sick leave

Upskilling, reskilling and certs

Job summary

EPAM Systems seeks a Senior Python AI Solution Engineer to design and deploy production-grade AI/LLM solutions. You will lead RAG pipelines, AI agent architectures, and API integration, partnering with leadership to shape project direction.

Strong Python expertise and cloud deployment experience are essential, with a focus on scalable, secure AI systems. You will collaborate across teams to translate business needs into robust technical implementations and drive experimentation, model tracking,

Qualifications

• 3+ years of professional software engineering experience with production AI and LLM apps.
• Proficiency in Python 3.11/3.12+ as the primary language.
• Expertise in LLM apps and agent frameworks like LangChain, LlamaIndex, and PydanticAI.
• Knowledge of Hugging Face Models/Datasets, sentence-transformers, and tokenizers.
• Familiarity with Python project/dependency tools such as uv, venv, and Poetry.
• Skills in code quality tools including Ruff, Pytest, and Jupyter.
• Background in ML libraries such as NumPy, pandas/Polars, and scikit-learn.
• Understanding of deep learning frameworks such as PyTorch and TensorFlow/Keras.
• Competency in vector search and RAG infra like FAISS, Qdrant, Chroma, Weaviate, Milvus, or pgvector with PostgreSQL.
• Experience with AI API and deployment tools such as FastAPI, Pydantic, and Uvicorn.
• Containerization/orchestration tools such as Docker and Kubernetes.
• Data infra tech like PostgreSQL, Redis, and Apache Kafka.
• English proficiency at B2 level or higher.

Responsibilities

• Design and build production-grade AI and LLM applications using Python.
• Develop and maintain RAG pipelines and AI agent architectures.
• Build and integrate APIs to support AI-driven solutions.
• Deploy and manage AI systems across cloud environments.
• Ensure secure and scalable system integration across platforms.
• Collaborate with customer Technical Leadership to define project direction and architecture.
• Apply analytical rigor to evaluate technical trade-offs and recommend solutions.
• Prototype and validate AI concepts using appropriate frameworks and tools.
• Support experimentation and model tracking throughout the development lifecycle.
• Translate business requirements into robust technical implementations.

Skills

Python

LLM/AI

LangChain

LlamaIndex

PydanticAI

HuggingFace

PyTorch

TensorFlow

NumPy

Pandas/Polars

scikit-learn

Jupyter

ML/DL basics

English

Tools

LangChain

LlamaIndex

PydanticAI

HuggingFace

PyTorch

TensorFlow

Keras

FastAPI

Uvicorn

Docker

Kubernetes

Poetry

Ruff

PyTest

PostgreSQL

Redis

Kafka

Jupyter

uv

Job description

We are seeking a Senior Python AI Solution Engineer with strong software engineering fundamentals and hands-on experience building production AI and LLM applications. The ideal candidate combines deep expertise in Python, RAG, AI agents, APIs, cloud services, system integration, and production deployment with sharp analytical thinking and sound decision-making. You will act as a trusted technical partner to customer leadership, helping guide the direction of AI initiatives.

Responsibilities

• Design and build production-grade AI and LLM applications using Python
• Develop and maintain RAG pipelines and AI agent architectures
• Build and integrate APIs to support AI-driven solutions
• Deploy and manage AI systems across cloud environments
• Ensure secure and scalable system integration across platforms
• Collaborate with customer Technical Leadership to define project direction and architecture
• Apply analytical rigor to evaluate technical trade-offs and recommend solutions
• Prototype and validate AI concepts using appropriate frameworks and tools
• Support experimentation and model tracking throughout the development lifecycle
• Translate business requirements into robust technical implementations

Requirements

• 3+ years of professional software engineering experience, with significant hands-on work in production AI and LLM applications
• Proficiency in Python 3.11/3.12+ as a primary development language
• Expertise in LLM application and agent frameworks such as LangChain, LlamaIndex, and PydanticAI
• Knowledge of Hugging Face Models/Datasets, sentence-transformers, and tokenizers
• Familiarity with Python project and dependency management tools such as uv, venv, and Poetry
• Skills in code quality tools including Ruff, Pytest, and Jupyter
• Background in machine learning libraries such as NumPy, pandas/Polars, and scikit-learn
• Understanding of deep learning frameworks such as PyTorch and TensorFlow/Keras
• Competency in vector search and RAG infrastructure such as FAISS, Qdrant, Chroma, Weaviate, Milvus, or pgvector with PostgreSQL
• Experience with AI API and deployment tools such as FastAPI, Pydantic, and Uvicorn
• Qualifications in containerization and orchestration tools such as Docker and Kubernetes
• Capability to work with data infrastructure technologies such as PostgreSQL, Redis, and Apache Kafka
• English proficiency at B2 level or higher

Nice to have

• Experience with TRL for LLM post-training
• Knowledge of DSPy for programmatic LLM pipelines
• Familiarity with LiteLLM for unified access to multiple LLM APIs
• Skills in experiment tracking tools such as MLflow and Weights & Biases
• Showcase of AI application UI development using Streamlit, Gradio, or FastAPI with React/Next.js/Angular 19+

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn