Time since we first saw it
Day 12
Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
Principal AI & Data Engineer
Reads like an AI Engineer role: building products on existing AI models.
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild and optimize RAG applications, including embeddings, prompts and evaluation
Design and deploy AI agents using LangChain, LangGraph, AutoGen and similar tools
Build and maintain data pipelines and streaming technologies
Design evaluation frameworks to measure model quality, accuracy and reliability
Implement CI/CD pipelines, testing and code quality controls
From the employer’s posting
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
Build and maintain robust data pipelines using modern data engineering practices and streaming technologies
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
Posting record
Report an errorActively hiringFirst seen by us 12 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 1, 202612 days ago
- Recorded sightings
- 14
- Last seen by us
- Nov 14, 2026
- Employer says posted
- Oct 23, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EPAM Systems is hiring
673 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- Azure
- Databricks
- Delta Lake
- Docker
- MLflow
- Spark
Where the posting names them
We are looking for a Principal AI & Data Engineer to join our team in London, UK in a hybrid working mode. 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. 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 Requirements 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 Nice to have 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
Your next step
Complete your application on careers.epam.com. The employer’s form will show what is required.
Already applied? Track this application
About EPAM Systems
- People
- About 3,012 in 2024.Benefit plan filings (Form 5500)
- Company
- Listed as EPAM.
- H-1B visas
- 21 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
We are looking for a Principal AI & Data Engineer to join our team in London, UK in a hybrid working mode. 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. 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 Requirements 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 Nice to have 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
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
UK
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- Work authorization
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