Lead Python AI Solution Engineer

EPAM Systems; Colombia; On-site; COP 194,200,000 - 291,300,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off and sick leave

Upskilling, reskilling and certificate

Job summary

EPAM Systems is seeking a Lead Python AI Solution Engineer to design and deliver production-grade AI and LLM applications. You will lead Python-based RAG and agent architectures, connect APIs, and collaborate with client leadership to steer architectural decisions.

The role emphasizes building scalable AI systems, deploying across cloud environments, and maintaining secure integrations while translating business needs into robust technical implementations.

Qualifications

• 5+ years of professional software engineering experience, including substantial hands-on delivery of production AI and LLM applications.
• High proficiency with Python 3.11/3.12+ as your primary programming language.
• Deep experience with LLM application and agent frameworks such as LangChain, LlamaIndex, and PydanticAI.
• Working knowledge of Hugging Face Models/Datasets, sentence-transformers, and tokenizers.
• Hands-on familiarity with Python project and dependency tooling such as uv, venv, and Poetry.
• Solid command of code quality and development tools including Ruff, Pytest, and Jupyter.
• Strong background with machine learning libraries such as NumPy, pandas/Polars, and scikit-learn.
• Practical understanding of deep learning frameworks such as PyTorch and TensorFlow/Keras.
• Proven track record implementing vector search and RAG infrastructure such as FAISS, Qdrant, Chroma, Weaviate, Milvus, or pgvector with PostgreSQL.
• Hands-on experience building AI APIs and deployment components with FastAPI, Pydantic, and Uvicorn.
• Demonstrated skills in containerization and orchestration using Docker and Kubernetes.
• Experience working with data infrastructure technologies such as PostgreSQL, Redis, and Apache Kafka.
• English proficiency at B2 level (Upper-Intermediate) or higher.

Responsibilities

• Design and deliver production-ready AI and LLM applications in Python.
• Develop and sustain RAG pipelines along with AI agent architectures.
• Implement and connect APIs that enable AI-driven capabilities.
• Deploy and operate AI systems across cloud environments.
• Ensure secure, scalable integration across platforms and services.
• Collaborate with client Technical Leadership to set project direction and architecture.
• Evaluate technical trade-offs with strong analytical judgment and recommend solutions.
• Prototype and prove AI concepts using the right frameworks and tools.
• Support experimentation and model tracking throughout the development lifecycle.
• Translate business requirements into dependable technical implementations.

Tools

Python

LangChain

LlamaIndex

PydanticAI

HuggingFace

sentence-transformers

tokenizers

uv

venv

Poetry

Ruff

Pytest

Jupyter

NumPy

pandas/Polars

scikit-learn

PyTorch

TensorFlow/Keras

FAISS

Qdrant

Chroma

Weaviate

Milvus

pgvector

PostgreSQL

FastAPI

Pydantic

Uvicorn

Docker

Kubernetes

PostgreSQL

Redis

Apache Kafka

Job description

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

Lead Python AI Solution Engineer to build production AI and LLM solutions, shape architecture and deliver reliable, scalable systems. You will lead Python-based RAG and agent work, integrate APIs, and partner with client technical leadership to steer decisions and delivery.

Responsibilities

• Design and deliver production-ready AI and LLM applications in Python
• Develop and sustain RAG pipelines along with AI agent architectures
• Implement and connect APIs that enable AI-driven capabilities
• Deploy and operate AI systems across cloud environments
• Ensure secure, scalable integration across platforms and services
• Collaborate with client Technical Leadership to set project direction and architecture
• Evaluate technical trade-offs with strong analytical judgment and recommend solutions
• Prototype and prove AI concepts using the right frameworks and tools
• Support experimentation and model tracking throughout the development lifecycle
• Translate business requirements into dependable technical implementations

Requirements

• 5+ years of professional software engineering experience, including substantial hands-on delivery of production AI and LLM applications
• High proficiency with Python 3.11/3.12+ as your primary programming language
• Deep experience with LLM application and agent frameworks such as LangChain, LlamaIndex, and PydanticAI
• Working knowledge of Hugging Face Models/Datasets, sentence-transformers, and tokenizers
• Hands-on familiarity with Python project and dependency tooling such as uv, venv, and Poetry
• Solid command of code quality and development tools including Ruff, Pytest, and Jupyter
• Strong background with machine learning libraries such as NumPy, pandas/Polars, and scikit-learn
• Practical understanding of deep learning frameworks such as PyTorch and TensorFlow/Keras
• Proven track record implementing vector search and RAG infrastructure such as FAISS, Qdrant, Chroma, Weaviate, Milvus, or pgvector with PostgreSQL
• Hands-on experience building AI APIs and deployment components with FastAPI, Pydantic, and Uvicorn
• Demonstrated skills in containerization and orchestration using Docker and Kubernetes
• Experience working with data infrastructure technologies such as PostgreSQL, Redis, and Apache Kafka
• English proficiency at B2 level (Upper-Intermediate) or higher

Nice to have

• Experience applying TRL for LLM post-training
• Knowledge of DSPy for building programmatic LLM pipelines
• Familiarity with LiteLLM to unify access to multiple LLM APIs
• Experience with experiment tracking tools such as MLflow and Weights & Biases
• Portfolio of AI application UI work 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

  We offer

  EPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.