Hybrid in The United Kingdom: LondonAI Solution EngineeringapplyWe're looking for a Senior AI Engineer – Data & AI Practice to join our team in London, UK, in a hybrid working mode.In this role, you will design and develop enterprise-scale AI applications leveraging Generative AI, Agentic AI and Retrieval-Augmented Generation (RAG) patterns. You will work on multi-agent orchestration, build reusable frameworks and deploy production-ready solutions that integrate advanced language models into business environments.This position requires a hands-on engineer who can combine technical expertise in AI platforms, distributed systems and data pipelines with effective collaboration skills. If you have a passion for deploying next-generation AI systems that deliver measurable business value, this is an opportunity to make an impact on innovative, enterprise-level AI capabilities.ResponsibilitiesDesign, build and deploy Generative AI and Agentic AI solutions from prototype to productionDevelop and optimize RAG pipelines including embeddings, hybrid search, prompt engineering and evaluation frameworksImplement AI agents using frameworks such as LangChain, LangGraph and AutoGen, integrating tools and enterprise workflowsApply modern AI engineering practices, ensuring reproducibility and production readiness in dynamic environmentsIntegrate solutions with enterprise data platforms and cloud services, focusing on scalability and governance standardsLeverage tools like Databricks, MLflow and Azure OpenAI for experimentation and deploymentApply DevOps best practices across CI/CD workflows, containerization and automated testing for robust deliveryDesign and maintain observability and monitoring solutions for AI systems using tools such as Langfuse or ArizePartner with stakeholders to align technical execution with business outcomes and provide technical guidance during architecture discussionsSupport team knowledge sharing and mentor engineers on AI best practices and delivery standardsRequirementsBachelor’s or Master’s degree in Computer Science, Engineering or related field; PhD is a plusProven hands-on experience with Generative AI frameworks, LLMs and agentic architecturesStrong practical knowledge of Databricks ecosystem including Delta Lake, Delta Live Tables and governance featuresProficiency in Python and working familiarity with SQL or ScalaExperience implementing RAG architectures and streaming solutions for AI pipelinesDeployment expertise on Azure or multi-cloud environments and familiarity with containerization tools such as DockerKnowledge of AI observability and evaluation solutions for monitoring and performance tuningStrong understanding of MLOps, CI/CD practices and infrastructure automation in AI engineering contextsDemonstrated ability to lead small teams and communicate effectively across technical and non-technical stakeholder groupsExperience managing end-to-end delivery from experimentation through production deployment in enterprise contextsNice to haveFamiliarity with vector databases such as Pinecone, Weaviate or MilvusKnowledge of AI governance protocols including safety guardrails and injection-prevention techniquesBackground working with event-driven architectures or distributed systemsExperience fine-tuning or training foundational models and applying advanced prompt engineering techniquesOUR BRANDS
AI Engineer - Data specialist employer: EPAM Systems
EPAM Systems is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the rapidly evolving field of AI. With a strong focus on employee growth, you will have access to extensive learning opportunities and benefits such as stock purchase plans, all while working remotely or in a hybrid model across Europe. Join us to make a meaningful impact in the energy and utilities sector, driving transformation strategies alongside industry leaders.
