Job Description The Gig This role sits at the intersection of enablement, innovation, and scaling—supercharging every engineer with advanced AI tools and workflows while exploring and prototyping the latest in AI developer technology. You'll also help standardise secure, high-performing AI environments across the business. If your background is primarily in data analysis, reporting, or BI, this role is unlikely to be a good fit. Responsibilities: Continuously explore, evaluate, and test emerging AI technologies to identify opportunities that could enhance engineering productivity and developer experience Monitor the performance, adoption, and effectiveness of existing engineering tools to understand usage patterns, gaps, and opportunities for improvement Build quick, effective prototypes, such as prompts or workflows that enable engineers to auto-generate Jira tasks, trigger background agents, and create PR-ready code with minimal input. Provide guidance and hands-on support to engineers looking to elevate their AI tooling skills Track and optimise AI tooling and infrastructure costs to ensure efficient, scalable, and sustainable usage across the engineering organisation. Care and commitment to information security practices to protect Healthengine and its customers About You You're the kind of person who takes accountability in a fast-paced, autonomous and flexible environment. Fast may be your default (like us!) but you never, ever compromise on what’s important, willing to take a steady, more informed approach when it comes to maintaining the trust of our team and customers. You handle change like a pro, and continuous improvement is a way of life. You are not afraid to speak up and share your thoughts respectfully, with the intention of making positive change. You take initiative and drive your own learning journey without waiting for someone to point you in the right direction. And ultimately, you care: about people, health and innovation. Experience you’ll bring: Demonstrated track record of delivery of major technical initiatives, particularly those focused on developer tooling or internal platforms. Typically 4 years successful execution at the Senior Engineer role or higher. Proven experience designing, building, and deploying AI-powered developer tools or workflows (e.g., code generation, task automation, prompt engineering). Hands-on experience with LLMs/Generative AI technologies and platforms (e.g., prompt development, fine-tuning, RAG architectures, model integration). Experience with engineering productivity metrics, monitoring, and optimization of internal tooling adoption and effectiveness. Experience using and implementing CI/CD systems, with an emphasis on automation within the SDLC. Demonstrated experience mentoring, training, and providing hands-on support to engineers on new tools and best practices. Familiarity with cloud platforms (e.g., AWS, GCP) and containerization technologies (e.g., Kubernetes) is a plus, but not the primary focus.
