AI & data engineer in energy trading

EPAM; Greater London; On-site; GBP 110,000 - 170,000; Full time

Benefits offered by this job

EPAM ESPP

Life insurance & income protection

Private medical & dental

Employee Assistance Program

Competitive pension

Commuter benefits & tech schemes

Learning & development & courses

Bonus & LTI programs

Job summary

EPAM is seeking a senior AI/data engineering leader to design, build and productionize enterprise-grade AI and GenAI solutions on Azure and Databricks. You will drive scalable AI apps, intelligent agents, and data-driven workflows powered by LLMs and modern AI frameworks.

You will lead hands‑on development of end-to-end data pipelines, RAG apps, and agent orchestration, while partnering with stakeholders to translate requirements into scalable, reliable solutions.

Qualifications

• Bachelor’s or Master’s degree in Statistics, Mathematics, Econometrics, Computer Science or a related field
• 8+ years of experience delivering data engineering, machine learning or AI solutions in enterprise environments
• Strong AI Data Engineering expertise with experience building production‑grade AI and GenAI systems
• Hands‑on experience with Azure AI Foundry, Azure cloud services and Databricks AI technologies
• Deep understanding of Large Language Models (LLMs) and Retrieval‑Augmented Generation (RAG) solutions
• Strong experience with MLflow, GenAI evaluation frameworks and model benchmarking methodologies
• Advanced programming skills in Python and SQL with strong knowledge of data modeling and ETL/ELT processes
• Solid understanding of Delta Lake, Delta Live Tables, Unity Catalog, Spark Structured Streaming and large‑scale data processing
• Experience with Azure Data Factory (ADF), Qlik Replicate and modern data architecture practices
• Excellent communication, stakeholder management, problem‑solving skills and commitment to high‑quality delivery
• Bonus: Experience with LangGraph, AutoGen or agent orchestration frameworks; governance, security and mentoring engineers

Responsibilities

• Develop and evaluate AI, GenAI and Agentic AI solutions using enterprise AI platforms and frameworks
• Build and optimize Retrieval‑Augmented Generation (RAG) applications, including embedding strategies, prompt engineering and evaluation processes
• Design, develop and deploy AI agents using frameworks such as LangChain, LangGraph, AutoGen and similar technologies
• Create scalable AI workflows using Databricks, MLflow, Azure AI Foundry and cloud‑native services
• Build and maintain robust data pipelines using modern data engineering practices and streaming technologies
• Deploy AI applications and services using Azure OpenAI, Azure AI Foundry, Databricks AI tools and Docker
• Design and execute evaluation frameworks to measure model quality, accuracy, reliability and reproducibility
• Implement CI/CD pipelines, testing frameworks, code quality controls and GitHub‑based development processes
• Collaborate with stakeholders to translate business requirements into scalable AI solutions
• Contribute to architecture decisions, technical roadmaps and backlog definition while supporting delivery from prototype to production

Skills

8+ years experience in data eng/ML/AI

AI Data Engineering

Python & SQL

LLMs & RAG

Azure AI Foundry & Databricks

MLflow & GenAI eval

ETL/ELT & data modeling

Delta Lake / Delta Live Tables / Unity

ADF & Qlik Replicate

Communication & stakeholder mgmt

Education

Bachelor’s or Master’s degree in Statistics/Math/CS

Tools

Azure Databricks

Azure AI Foundry

Databricks AI tools

MLflow

Qlik Replicate

Docker

LangChain / LangGraph / AutoGen

Job description

Описание:

In this role, you will design, build and productionize enterprise-grade AI and GenAI solutions on Azure and Databricks platforms. You will develop scalable AI applications, intelligent agents and data-driven solutions powered by large language models and modern AI frameworks. The role requires hands‑on expertise in AI data engineering, cloud technologies and GenAI adoption while driving innovation, reliability and scalability across enterprise environments.

Задачи:

• Develop and evaluate AI, GenAI and Agentic AI solutions using enterprise AI platforms and frameworks
• Build and optimize Retrieval‑Augmented Generation (RAG) applications, including embedding strategies, prompt engineering and evaluation processes
• Design, develop and deploy AI agents using frameworks such as LangChain, LangGraph, AutoGen and similar technologies
• Create scalable AI workflows using Databricks, MLflow, Azure AI Foundry and cloud‑native services
• Build and maintain robust data pipelines using modern data engineering practices and streaming technologies
• Deploy AI applications and services using Azure OpenAI, Azure AI Foundry, Databricks AI tools and Docker
• Design and execute evaluation frameworks to measure model quality, accuracy, reliability and reproducibility
• Implement CI/CD pipelines, testing frameworks, code quality controls and GitHub‑based development processes
• Collaborate with stakeholders to translate business requirements into scalable AI solutions
• Contribute to architecture decisions, technical roadmaps and backlog definition while supporting delivery from prototype to production

Требования:

• Bachelor’s or Master’s degree in Statistics, Mathematics, Econometrics, Computer Science or a related field
• 8+ years of experience delivering data engineering, machine learning or AI solutions in enterprise environments
• Strong AI Data Engineering expertise with experience building production‑grade AI and GenAI systems
• Hands‑on experience with Azure AI Foundry, Azure cloud services and Databricks AI technologies
• Deep understanding of Large Language Models (LLMs) and Retrieval‑Augmented Generation (RAG) solutions
• Strong experience with MLflow, GenAI evaluation frameworks and model benchmarking methodologies
• Advanced programming skills in Python and SQL with strong knowledge of data modeling and ETL/ELT processes
• Solid understanding of Delta Lake, Delta Live Tables, Unity Catalog, Spark Structured Streaming and large‑scale data processing
• Experience with Azure Data Factory (ADF), Qlik Replicate and modern data architecture practices
• Excellent communication, stakeholder management, problem‑solving skills and commitment to high‑quality delivery
• Будет плюсом: Experience in commodity trading and supply operations, ideally within the energy sector; Experience with Microsoft Copilot Studio, Databricks Mosaic AI, Agent Bricks or Genie; Experience with LangGraph, AutoGen or other agent orchestration frameworks; Familiarity with enterprise AI governance, security and compliance practices; Experience leading technical teams, defining technical strategy and mentoring engineers

Условия:

• EPAM Employee Stock Purchase Plan (ESPP)
• Protection benefits including life assurance, income protection and critical illness cover
• Private medical insurance and dental care
• Employee Assistance Program
• Competitive group pension plan
• Cyclescheme, Techscheme and season ticket loans
• Various perks such as free Wednesday lunch in‑office, on‑site massages and regular social events
• Learning and development opportunities including in‑house training and coaching, professional certifications, and courses
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long‑Term Incentive (LTI) Program