Senior AI/ML Engineer: Generative AI & MLOps (Hybrid)

Bupa UK; Salford; Hybrid; GBP 41,000 - 55,000; Full time

Benefits offered by this job

25 days holiday

Bupa health insurance

Enhanced pension & life cover

Annual bonus

Onsite gyms / local discounts

Flexible working

Job summary

Bupa is seeking a Senior AI/ML Engineer to join our Applied AI team in a hybrid role based in the UK. You will bridge research and production, delivering scalable AI and ML solutions that drive real business value.

You’ll lead end-to-end work on Generative AI and Agentic AI, deploy across Azure and Snowflake, implement MLOps, and mentor colleagues while embedding responsible AI practices.

Qualifications

• Proven experience designing, building and deploying AI/ML solutions to production.
• Strong background in MLOps and end-to-end AI lifecycle governance.
• Deep understanding of Generative AI and Agentic AI concepts and runtimes.

Responsibilities

• Bridge experimentation to production, ensuring scalable, secure AI systems.
• Design and deploy end-to-end AI/ML solutions from data prep to monitoring.
• Develop and maintain robust MLOps frameworks and governance.
• Develop Generative AI and Agentic AI solutions (RAG, embeddings, vector search).
• Work with LangGraph, LlamaIndex, and AI frameworks; deploy on Azure/GCP/Snowflake.
• Mentor junior colleagues and promote engineering best practices.

Skills

Python

CI/CD

GitHub Actions

Azure DevOps

Docker

Kubernetes

Stakeholder management

MLOps

Education

Bachelor's degree in CS/Math/Stats

Master's degree in Data Science/Analytics

Tools

LangChain

LangGraph

LlamaIndex

Cre wAI

Autogen

Google ADK

Job description

Bupa is seeking a Senior AI/ML Engineer to join our Applied AI team in a hybrid role based in the UK. You will bridge research and production, delivering scalable AI and ML solutions that drive real business value.

You’ll lead end-to-end work on Generative AI and Agentic AI, deploy across Azure and Snowflake, implement MLOps, and mentor colleagues while embedding responsible AI practices.