AI Engineer - Data specialist

Responsibilities

• Design, build and deploy Generative AI and Agentic AI solutions from prototype to production
• Develop and optimize RAG pipelines including embeddings, hybrid search, prompt engineering and evaluation frameworks
• Implement AI agents using frameworks such as LangChain, LangGraph and AutoGen, integrating tools and enterprise workflows
• Apply modern AI engineering practices, ensuring reproducibility and production readiness in dynamic environments
• Integrate solutions with enterprise data platforms and cloud services, focusing on scalability and governance standards
• Leverage tools like Databricks, MLflow and Azure OpenAI for experimentation and deployment
• Apply DevOps best practices across CI/CD workflows, containerization and automated testing for robust delivery
• Design and maintain observability and monitoring solutions for AI systems using tools such as Langfuse or Arize
• Partner with stakeholders to align technical execution with business outcomes and provide technical guidance during architecture discussions
• Support team knowledge sharing and mentor engineers on AI best practices and delivery standards

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering or related field; PhD is a plus
• Proven hands-on experience with Generative AI frameworks, LLMs and agentic architectures
• Strong practical knowledge of Databricks ecosystem including Delta Lake, Delta Live Tables and governance features
• Proficiency in Python and working familiarity with SQL or Scala
• Experience implementing RAG architectures and streaming solutions for AI pipelines
• Deployment expertise on Azure or multi-cloud environments and familiarity with containerization tools such as Docker
• Knowledge of AI observability and evaluation solutions for monitoring and performance tuning
• Strong understanding of MLOps, CI/CD practices and infrastructure automation in AI engineering contexts
• Demonstrated ability to lead small teams and communicate effectively across technical and non-technical stakeholder groups
• Experience managing end-to-end delivery from experimentation through production deployment in enterprise contexts

Nice to have

We offer/Benefits

• 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