Generative AI Engineer · Hybrid

• Design, develop, and deploy Generative AI applications across healthcare use cases.
• Build solutions using LLMs, RAG pipelines, AI agents, voice AI, and workflow automation technologies.
• Partner with healthcare and operational stakeholders to identify and solve business challenges with AI.
• Own the full product lifecycle, from ideation and experimentation through to production deployment and optimisation.
• Develop scalable backend services, APIs, and production-grade AI systems.
• Monitor, improve, and scale AI products based on user feedback and performance metrics.
• Contribute to technical excellence through code reviews, best practices, and architecture discussions.

We’re building AI-powered products that make a genuine impact across healthcare operations and patient services. From intelligent patient support assistants handling thousands of interactions each week to AI tools that help clinicians and operational teams access and process critical information faster, our solutions are deployed, measured, and continuously improved in real-world environments. We don’t build proof-of-concepts that sit on a shelf. We take ideas from discovery to production, iterate rapidly, and focus on creating measurable value for healthcare professionals and patients alike. If you have 2-5 years of experience building AI applications and want to work on products used at scale, we’d love to hear from you., * 2-5 years’ experience building AI applications or machine learning products.

• Experience with LLMs, Retrieval-Augmented Generation (RAG), AI agents, fine-tuning, voice AI, or similar AI technologies.
• Strong Python development experience with production-level software engineering skills.
• Experience working with cloud platforms such as Azure, AWS, or Google Cloud.
• Knowledge of APIs, software development best practices, testing, and deployment processes.
• Experience delivering products or features used by real customers or end users.

Preferred Experience

• Experience with vector databases and document intelligence solutions.
• Familiarity with agentic AI frameworks and multi-agent systems.
• Exposure to MLOps, AI monitoring, and model deployment practices.
• Experience with Databricks or similar AI and data platforms.
• Previous experience working within healthcare or other regulated industries.