At a Glance
- Tasks: Design and develop cutting-edge AI solutions to tackle real-world business challenges.
- Company: Join a leading tech firm at the forefront of AI innovation.
- Benefits: Enjoy competitive pay, health perks, remote work options, and growth opportunities.
- Other info: Dynamic team culture with exciting projects and regular social events.
- Why this job: Be part of a high-growth environment pushing the boundaries of AI technology.
- Qualifications: 4+ years in AI engineering or data science with strong Python skills.
The predicted salary is between 70000 - 90000 £ per year.
We're looking for a Senior AI Engineer / Data Scientist to join our team in London, United Kingdom, in a hybrid working mode. This role is at the core of EPAM’s Data & AI Practice and focuses on building state-of-the-art Generative AI, Agentic AI, and advanced data science solutions for real-world business problems. You’ll design and develop multi-agent systems, implement RAG pipelines, and deliver production‑ready AI applications that transform client capabilities across multiple industries. If you're passionate about pushing the frontiers of LLMs, orchestration frameworks, and scaling AI systems into production, this opportunity offers a high‑growth environment and cutting‑edge challenges.
Responsibilities
- Design, build, and deploy Generative AI and Agentic AI solutions from prototyping through production
- Develop and optimize multi‑agent systems using frameworks such as LangGraph, CrewAI, AutoGen, and Semantic Kernel
- Implement orchestration patterns including planner/executor, supervisor/worker, and tool‑calling workflows
- Design and build RAG pipelines, including embeddings, chunking, hybrid search, and retrieval evaluation for enterprise data grounding
- Develop orchestration engines supporting multi‑step planning, delegation, and fallback paths for agent workflows
- Implement integration and communication patterns via MCP, A2A, OpenAPI, REST, and gRPC
- Build production‑grade Python APIs and microservices integrating with enterprise systems and AI services
- Apply observability and monitoring solutions (Langfuse, Arize, Grafana) to ensure system reliability
- Contribute to solution architecture, best engineering practices, and documentation
Requirements
- Bachelor’s/Master’s in Computer Science, Data Science, or related field with 4+ years’ experience, or Ph.D. with relevant experience
- Strong engineering experience with Python, APIs, microservices, debugging, and code review
- Proven experience building and deploying Generative AI or Agentic AI applications in production
- Deep understanding of LLM concepts, RAG patterns, prompt design, and evaluation methodologies
- Experience with multi‑agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel)
- Familiarity with orchestration strategies like planner/executor and tool calling
- Knowledge of MCP, A2A protocols, and OpenAPI‑based integration methods
- Strong experience with cloud environments, ideally Azure (Azure OpenAI, AI Foundry, AI Search)
- Competence in containerized deployments, CI/CD, and MLOps tooling (MLFlow, Airflow)
Nice to have
- Experience with Microsoft Agent Framework, Azure AI Agent Service
- Knowledge of vector databases (Pinecone, Weaviate, Qdrant, Milvus)
- Familiarity with guardrail and AI safety techniques (output filtering, prompt injection defense)
- Experience in distributed systems, event‑driven architectures, and workflow engines
- Prior involvement in training, fine‑tuning, or experimenting with foundation models
We offer
- 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
- 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
Senior AI Engineer / Data Scientist employer: EPAM Systems
At EPAM, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. As a Senior AI Engineer / Data Scientist, you'll benefit from a hybrid working model, competitive compensation, and a comprehensive benefits package that includes private medical insurance, employee stock purchase plans, and extensive learning opportunities to support your professional growth. Join us to tackle cutting-edge challenges in AI while enjoying perks like free lunches, on-site massages, and a vibrant social atmosphere.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer / Data Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to Generative AI and multi-agent systems. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common interview questions and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining us.
We think you need these skills to ace Senior AI Engineer / Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior AI Engineer / Data Scientist role. Highlight your experience with Generative AI, multi-agent systems, and any relevant projects you've worked on.
Craft a Compelling Cover Letter:Your cover letter is your chance to show us your passion for AI and data science. Share specific examples of how you've tackled real-world problems using AI solutions and why you're excited about joining our team.
Showcase Your Technical Skills:Don’t forget to mention your proficiency in Python, APIs, and cloud environments like Azure. We want to see how you’ve applied these skills in production settings, so be specific about your achievements.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity in our hybrid working environment.
How to prepare for a job interview at EPAM Systems
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, APIs, and multi-agent orchestration frameworks. Brush up on your knowledge of Generative AI and Agentic AI applications, as well as RAG pipelines. Being able to discuss these topics confidently will show that you're not just a fit for the role but also genuinely passionate about the work.
✨Prepare Real-World Examples
Think of specific projects or experiences where you've successfully built or deployed AI solutions. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will help demonstrate your problem-solving skills and practical experience, which are crucial for this role.
✨Understand the Company’s Vision
Research EPAM’s Data & AI Practice and understand their approach to AI solutions. Familiarise yourself with their recent projects or innovations in the field. This knowledge will allow you to tailor your answers and show how your goals align with the company’s mission, making you a more attractive candidate.
✨Ask Insightful Questions
Prepare thoughtful questions to ask during the interview. Inquire about the team dynamics, the challenges they face in deploying AI solutions, or how they measure success in their projects. This not only shows your interest in the role but also helps you gauge if the company is the right fit for you.
