/ML & AI Engineer

ML & AI Engineer

London, England, GBRemotegbvia direct
// Job Type
Full Time
// Salary
Not disclosed
// Posted
2 months ago
// Seniority
mid
// Work Mode
hybrid
// Experience
2+ years

About the Role

​Job Title: ML & AI Engineer Location: London- 3Days/week Onsite Duration: 6months+ Contract Inside IR35 Job Overview We are looking for an ML & AI Engineer to support the development of advanced AI-driven solutions for conversational banking and customer engagement. The role involves building AI products, developing agentic workflows, and integrating AI systems with banking platforms across cloud environments. Key Responsibilities Develop and provision infrastructure to support agentic workflows across Azure and GCP environments. Contribute to the design and development of AI solutions, including the Coach AI and AI Assistant platforms. Build agent integration patterns that enable systems to perform actions on behalf of customers using banking systems. Develop new AI products within the Conversational Banking Lab. Key initiatives include: Agent summarisation – building features that summarise complex conversations. App search evolution – transforming vector search into a generative AI experience with a unified user interface. Evaluation methods – automating testing and evaluation of both deterministic and generative AI conversations. Required Skills Must Have Python – minimum 2+ years experience building production-grade LLM applications. Strong software engineering fundamentals, including microservices architecture, CI/CD pipelines, and event-driven architecture. AI Engineering experience including: RAG pipelines Prompt engineering Vertex AI LLMOps and monitoring/evaluation of AI systems Data Engineering experience building scalable pipelines using Python or Spark. Experience with GCP services such as BigQuery, Spanner, Dataflow, and Firestore. Nice to Have Experience with Agentic AI frameworks such as LangGraph, ADK, CrewAI, or multi-agent architectures. Experience designing deployable AI solutions (beyond notebook-based experimentation). Knowledge of data ontologies and graph-based data storage and retrieval. Experience working in Agile/Scrum environments. ​ If this position is of interest, we'd love to hear from you!

Tech Stack

Pythonmicroservices architectureCI/CD pipelinesevent-driven architectureRAG pipelinesPrompt engineeringVertex AILLMOpsmonitoring/evaluation of AI systemsData EngineeringSparkGCPBigQuerySpannerDataflowFirestore

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