AI Engineer
- Design and deploy production agentic AI workflows, including orchestration, tool use, retrieval and data querying.
- Evaluate and improve AI quality, robustness, safety, security, cost and latency in production.
- Collaborate across engineering and product teams to integrate AI capabilities and shape technical direction.
AI Engineer
About the company
Our client is a global leader in healthcare, providing innovative products to thousands of customers across the globe. Its customers range from community clinics to some of the most respected names in their fields, who utilise their products to make a real difference to their customers lives.
Driven by a multidisciplinary team of researchers, clinicians, scientists, designers, developers and engineers, its products give health professionals clear, objective insight into the people they care for.
About the role
The business has built one of the largest and most valuable datasets in its field, and it continues to grow. Utilising critical data points, they are seeking an impressive Engineer with experience across AI to help shape the future.
In this role, you will
- Build agentic capabilities: design and ship production agent workflows, covering orchestration, tool calling, MCP servers, skills and context management.
- Ground AI in data: build retrieval, search and data querying capabilities across modern data platforms, including Snowflake and Databricks.
- Own production quality: design and evolve evaluation, monitor quality, feedback, cost and latency, and improve accuracy and robustness.
- Build in safety and security: implement guardrails that keep responses within agreed scope and ensure each customer's data and context remain securely isolated.
- Ship through automation: deploy AI components through version-controlled pipelines, promoted consistently across environments and regions.
- Integrate across teams: work with data engineering, platform and deployment teams to bring AI capabilities into the wider product suite.
- Shape what gets built: influence architecture and product decisions, and actively look for ways to improve robustness.
What they are looking for
This is a practical engineering role seeking hand's on engineer who can also support strategic direction. You could some from any background across Software, Cloud, Data etc...What is more important is that you have devevloped your experience into a hand's on role where you have experience shipping agentic AI with a track record applying LLMs and ideally text to SQL.
- Strong software engineering skills in modern languages (Azure, AWS, SQL, Python etc), with the depth to own your work through deployment and operation.
- A track record of taking LLM-powered or agentic products into production.
- Hands-on experience evaluating AI systems and using the results to guide decisions.
- Practical experience with retrieval, tool use and agent design.
- Clear communication skills, including explaining trade-offs to non-technical stakeholders
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Skills
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