Senior Software Engineer – Clinical AI

Responsibilities

• Build end-to-end AI features: Architect and ship fullstack solutions (from React frontends to Python backend services) that leverage our voice AI and LLMs to automate clinical workflows.
• Operationalise Voice AI: Implement and fine-tune audio processing pipelines, ensuring our Automatic Speech Recognition (ASR) and LLM agents perform accurately in diverse, real-world medical environments.
• Bridge the gap between model and product: Translate complex feedback from clinicians into technical solutions, rapidly prototyping and deploying improvements to model behaviour, prompting strategies, and audio handling.
• Optimise for real-time interaction: Tune fullstack performance to handle real-time audio streaming and token generation, minimising latency, so clinicians have a seamless conversational experience.
• Partner with implementation and clinical teams: Shorten the feedback loop by shipping critical integrations and feature requests from concept to production in days, not quarters.

Qualifications

• Mastery of Fullstack fundamentals: You are equally proficient in Python and modern frontend frameworks (React/TypeScript), capable of owning a feature from the database schema to the UI interaction.
• Applied AI & Voice fluency: You have a working knowledge of LLM integration (RAG, prompt engineering) and audio technologies (ASR, speech processing) and know how to build around their probabilistic nature.
• Pragmatic problem solving: You balance engineering purity with the need for speed; you know when to build a robust system and when to ship a tactical solution to unblock a customer.
• Cloud fluency (AWS or GCP): You can spin up your own infrastructure (containers, serverless functions) and manage CI/CD pipelines to get your code into the hands of users independently.
• Rigorous testing in production: You understand that "works on my machine" isn't enough; you implement observability and feedback loops to monitor how your AI features perform in the wild.
• Medical degree with clinical experience, and ideally experience working on clinical AI products.