Technical Implementation Specialist at Thyme Care

  • Company: Thyme Care
  • Location: Remote
  • Salary: $140K – $155K
  • Job type: full time
  • Workplace: remote
  • Posted: 2026-06-06

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Job description

Our Mission We exist to create a more connected, compassionate, and confident experience for people with cancer and those who care for them. We make it easier to get answers, access high-quality care quickly, and feel supported throughout treatment and beyond. Today, Thyme Care is a market-leading value-based oncology care enabler, partnering with national and regional health plans, providers, and employers to deliver better outcomes and lower costs for thousands of people across the country. Our model combines high-touch human support with powerful technology and AI to bring together everyone involved in a person’s cancer journey: caregivers, oncologists, health plans, and employers. As a tech-native organization, we believe technology should strengthen the human connection at the center of care. Through data science, automation, and AI, we simplify complexity, improve collaboration, and help care teams focus on what matters most: supporting people through cancer. Looking ahead, our vision is bold: to become a household name in cancer care, where every person diagnosed asks for Thyme Care by name. If you’re inspired to make cancer care more human and to help reimagine what’s possible, we’d love to meet you. Together, we can build a future where every person with cancer feels truly cared for, in every moment that matters. What You’ll Do In this role, you'll sit at the intersection of product development and care delivery — translating complex clinical and operational processes into our purpose-built tools to support our care team in their day-to-day work. You'll partner closely with a service designer who works with operations teams to understand and map new processes onto our tools. You’ll focus on the technical implementation and productization of those processes, ensuring that your approach serves the care team, engineering, and data science. Your work will span creative implementation within our current tooling, maintaining and curating what exists, and helping shape the product direction that will evolve these tools to better support care teams over time. Day-to-day, you will: • Execute configurations in close collaboration with a service designer, including forms, automations, and our proprietary tasking system • Build structured documentation systems to support clean data capture, with conditional logic and extensibility in mind • Build and test automations within Thyme Box, accounting for edge cases • Build tasking that clearly and cleanly maps out complex, branching processes • Investigate bugs and unexpected behavior, educate users on underlying logic, and build towards transparency and understandability • Audit and maintain existing configurations: improving consistency, defining best practices, deprecating what is outdated, and building for scale What Leads to Success • Product and technical foundations . You have relevant experience with digital products — as a product manager, product designer, or in a technical implementation role. While not necessarily an engineer, you understand web applications and can read, debug, and write simple code. You think like an engineer about data models, edge cases, and downstream impacts of implementation decisions. Where you may not have the skillset or expertise in a particular area today, you are willing to invest time to learn. • Detail orientation . You can juggle a high volume of requests without sacrificing organization or accuracy. You document carefully and communicate proactively. You don’t let details slip. • Systems stewardship . You take ownership of our tools as living systems — not just building, but curating on an ongoing basis. Naming conventions and consistency matter to you. You proactively address technical debt, define best practices, and push back when a short-term request would create long-term disorder. • Creative problem solving . When a request fits neatly into existing patterns, you execute with precision. When it doesn't, you quickly generate scrappy s

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