Intermediate Software Engineer-Internal Platform & AI Enablement (Auckland,NZ)

About Rhapsody: 
Healthcare is innovating fast and AI is accelerating the pace. But AI is only as good as the data it can securely access. Today, moving data between providers, payers, and digital health innovators is still harder than it should be, and inconsistent data quality creates risk, rework, and stalled initiatives.

Our mission is to accelerate innovation by reducing the burden of data access and data quality so teams can build, deploy, and scale solutions with confidence. Rhapsody provides behind-the-scenes interoperability and data quality foundation that helps information move reliably between systems, across formats, and at the speed modern healthcare demands.

Most people won’t ever see our products during a medical visit (that’s infrastructure). Think of Rhapsody as the connective tissue and increasingly, the “data readiness” layer that enables digital transformation, analytics, and AI initiatives by making data accessible, trustworthy, and actionable.

At Rhapsody, we are an AI-first company, meaning we actively use and embrace artificial intelligence to enhance how we work, collaborate, and deliver. We expect our team members to be open to adopting AI tools in their roles, continuously exploring ways to work smarter, improve efficiency, and drive innovation while maintaining high standards of quality, security, and ethical responsibility.

If you want to help solve one of healthcare’s hardest problems, turning fragmented data into safe, usable information—apply at rhapsody.health.

Candidate must be local to Auckland, NZ

About the role 

We’re looking for a high-performing software engineer to become the first dedicated member of our Internal Platform and AI Enablement function. 

This is a force-multiplier role. Your job is not simply to ship code, but to improve the systems, workflows, and guardrails that allow every engineer to build, verify, ship, and support software more effectively. You’ll work closely with our existing Lead Engineers, who will help set direction and priorities in the early stages. Over time, we expect this role to grow in scope and autonomy, with a pathway into leading this function as it matures. 

This role exists to help turn AI from individual experimentation into organisational capability. As AI-assisted and agentic software engineering becomes a standard part of how modern teams work, the real differentiator is no longer access to AI tools alone. It is the strength of the internal platform, the clarity of the engineering workflows, the quality of the internal context available to humans and tools, and the reliability of the feedback loops that sit around them. This role sits at the centre of that shift.  

Business outcomes this role is expected to influence 

Deliver better value to our customers, sooner, safer and happier by:

Increasing engineering throughput without sacrificing quality or control  

Reducing friction in local development, CI/CD, testing, release, and production support  

Improving consistency and trust in AI-assisted engineering workflows  

Reducing dependency on tribal knowledge by improving documentation, standards, templates, and self-service workflows  

Strengthening the foundations for safe, measurable adoption of AI across software delivery  

Creating reusable platform capabilities that scale productivity gains across the whole engineering organisation  

What you’ll do 

Partner with Lead Engineers to shape the first wave of internal platform, developer experience, and AI enablement improvements.  

Build and improve the engineering “paved road,” including local development, CI/CD, test automation, release workflows, observability, service templates, internal tooling, and engineering documentation.  

Improve the day-to-day experience of building software, from setting up a local dev environment to debugging a production issue.  

Help shape the systems, repository conventions, documentation, and workflows that make AI-assisted development more useful, reliable, and easier to govern in practice.  

Improve the quality and accessibility of internal engineering context so that both engineers and approved AI tools can work more effectively with company-specific knowledge.  

Contribute to practical AI enablement initiatives such as workflow guidance, reusable patterns, lightweight evaluation and quality checks, and safe usage guardrails in the software delivery lifecycle.  

Identify recurring sources of developer friction and turn them into simple, scalable improvements that reduce cognitive load and improve engineering flow.  

Contribute across backend systems, tooling, automation, and infrastructure as needed. Lead by example in the use of AI-assisted and agentic ways of working, using approved AI tools and agents as a normal part of how you analyse problems, design solutions, write code, generate tests, document systems, and automate repetitive tasks 

Help create consistent ways of working that improve reliability, maintainability, and developer confidence.  

Gather feedback from engineers, understand where time and energy are being lost, and turn that into high-impact platform and DevEx improvements.  

Measure the impact of your work through practical indicators such as setup time, build times, CI stability, deployment confidence, onboarding speed, workflow adoption, and reduction in repeated friction points.

What success looks like 

In your first few months, you’ll build trust across the engineering team, understand the highest-friction developer journeys, and deliver a small number of visible improvements that make engineers’ lives easier. You’ll also quickly establish yourself as someone who uses AI and agents effectively in your own work, and who can translate that into practical, credible examples for others. 

Within 6 to 12 months, you’ll be a trusted owner of meaningful parts of the internal platform and DevEx roadmap. Engineers should feel the difference in faster feedback loops, clearer standards, more reliable tooling, and a more effective way of working with AI in day-to-day software delivery. 

Over time, you’ll grow from an engineer taking direction from existing leads into someone who helps lead this function technically and culturally. 

Who you are 

Humble: low ego, open to feedback, and focused on team outcomes over personal credit.  

Hungry: proactive, curious, eager to learn, and motivated by solving important problems.  

Smart: strong engineering fundamentals, sound judgment, and a talent for simplifying complexity.  

A servant leader: you naturally look for ways to unblock others, improve the system around them, and raise the effectiveness of the wider team.  

A team player: collaborative, generous with context, and committed to shared success.  

Comfortable with ambiguity: excited by the opportunity to help shape a new function rather than inherit a fully defined one.  

Practical: you care about real-world adoption and outcomes, not platform or AI for their own sake. 

What you bring 

Strong software engineering experience in production environments. This role is aimed at someone operating at the top end of intermediate level, typically with over 5 years of  experience, with the judgment and maturity to grow into a lead role over time.  

Solid coding ability in at least one modern programming language, and the ability to work across systems, tooling, and automation.  

Experience improving developer workflows, delivery systems, or internal tools, whether from a product engineering, platform, infrastructure, SRE, or DevEx background.  

Practical experience in some of the following areas: CI/CD, cloud infrastructure, infrastructure as code, observability, test automation, release engineering, service frameworks, or developer tooling.  

The ability to work closely with senior technical leaders, take direction well, and still show strong initiative and ownership.  

Strong written and verbal communication skills.  

Good taste in simplicity, maintainability, developer ergonomics, and operational quality.  

A genuine interest in helping teams use AI-assisted development tools effectively, safely, and in ways that improve the overall engineering system.  

Leads AI-first engineering by redesigning development workflows, orchestrating agent-based tools, and building scalable automations integrated into core systems (e.g., CI/CD, testing, incident response).

Drives team-wide impact by setting standards, mentoring adoption, and delivering measurable gains in velocity, code quality, and reliability through advanced, multi-agent execution.

Rhapsody provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.