Principal AI Data Engineer

EPAM Systems, Inc.; Greater London; Hybrid; GBP 110,000 - 140,000; Full time

Benefits offered by this job

ESPP

Private medical insurance

Company pension plan

On-site massages

Free lunch

Job summary

EPAM Systems, Inc. in London is seeking a Principal AI Data Engineer to design and implement advanced AI and GenAI solutions that deliver real business impact.

You will work across architecture, engineering and research to build data and AI-enabled platforms, ensuring scalable solutions for enterprise environments and contributing to sprint planning within an agile team.

Qualifications

• 8+ years of experience in data science and AI projects.
• Deep understanding of large language models (GPT, Llama, Claude, Mistral) and their reasoning capabilities.
• Databricks experience including DLT, Delta Lake and Unity Catalog governance.
• Spark Structured Streaming and Autoloader awareness.
• Proficiency in Python, SQL or Scala.

Responsibilities

• Develop and evaluate AI/GenAI/AgenticAI prototypes.
• Build and optimize Retrieval-Augmented Generation systems with embedding models and prompt engineering.
• Design and deploy basic AI agents using LangChain, AutoGen and smolagents.
• Follow DevOps practices including CI/CD, testing, and GitHub workflows.
• Write modular Python code using OOP and frameworks like Pydantic and PyTorch.

Skills

Python programming

SQL

Scala

PyTorch

Data modeling

ETL/ELT

DevOps

Git & CI/CD

Spark Structured Streaming

Education

Bachelor's or Master's in Statistics/Mathematics/Econometrics

Tools

Databricks

LangChain

AutoGen

smolagents

PyTorch

Docker

Job description

We're looking for a Principal AI Data Engineer to join our team in London, United Kingdom in a hybrid working mode. In this role, you will design and implement advanced AI and GenAI solutions that deliver real business impact. You will work across architecture, engineering and research to build data and AI-enabled platforms, ensuring performance and scalable solutions that accelerate digital transformation for enterprise environments.ResponsibilitiesDevelop and evaluate AI/GenAI/AgenticAI prototypes using tools such as Copilot Studio, AI Foundry, Copilot Analyst Agent, Mosaic AI, Genie, AgentBricks and MLflowBuild and optimize Retrieval-Augmented Generation (RAG) systems including embedding model selection, prompt engineering and traceable evaluationDesign and deploy basic AI agents using frameworks such as LangChain, AutoGen and smolagentsDeploy models and applications leveraging Azure OpenAI, Azure AI Foundry, Databricks Mosaic Gateway and containerization with DockerFollow DevOps best practices including CI/CD pipelines, testing, linting and GitHub workflowsWrite modular reusable Python code using OOP design patterns and frameworks such as Pydantic and PyTorchEmphasize reproducibility, open-source practices and performance tuning in end-to-end deliveryOperate within agile teams, contributing to sprint planning and collaborative reviewsBuild scalable AI workflows and architectures using tools like Databricks, Genie and LangChainLead architectural planning and backlog creation to ensure long-term reliability and maintainabilityRequirementsBachelor’s or Master’s degree in Statistics, Mathematics, Econometrics or similar discipline8+ years of experience in data science and AI projectsDeep understanding of large language models (GPT, Llama, Claude, Mistral) and their reasoning capabilitiesStrong experience with Databricks including DLT, Delta Lake and Unity Catalog governanceSolid knowledge of streaming technologies such as Spark Structured Streaming and AutoloaderProficiency in programming with Python, SQL or ScalaExpertise in data modeling, ETL/ELT processes and data architectureGood understanding of DevOps practices including Git standards and CI/CD automationExperience working in Azure cloud environmentsFamiliarity with GenAI evaluation frameworks, benchmarking and testing methodologiesExcellent problem-solving, communication and stakeholder management skillsNice to haveUnderstanding of enterprise AI governance modelsHands-on experience with Microsoft Copilot, AI Foundry, Databricks MosaicAI and AgentBricksStrong decision-making capabilities and conflict resolution skillsProven ability to identify and mitigate risks in data-centric projectsFamiliarity with commercial operations in trading and supply environmentsWe offerEPAM Employee Stock Purchase Plan (ESPP)Protection benefits including life assurance, income protection and critical illness coverPrivate medical insurance and dental careEmployee Assistance ProgramCompetitive group pension planCyclescheme, Techscheme and season ticket loansVarious perks such as free Wednesday lunch in-office, on-site massages and regular social eventsLearning and development opportunities including in-house training and coaching, professional certifications, and coursesIf otherwise eligible, participation in the discretionary annual bonus programIf otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program