Engineering Lead, Clinical Operations

At Clover, the Business Enablement team leads our technological advancement while ensuring robust security and compliance. We deliver user-friendly corporate applications, manage complex data ecosystems, and provide efficient tech solutions across the organization. Our goal is simple: we make it easy for the business to do what’s right for Clover.

A likely first assignment is an “Air Traffic Control” system for field operations. A supervisor needs to understand what is happening and act when the plan breaks: a flat tire, a delayed visit, a missing piece of equipment, or a member whose availability changes. You will work with the people doing the job to decide what they need to see, what the system can help resolve, and when a human should intervene.

This is a hands-on role that spans product and engineering. You will understand the business problem, shape the solution, build useful increments, and see whether they work. You may start without direct reports and can expect to coach and eventually manage one or two engineers. You should enjoy building personally and helping others become more capable.

We value a tinkering instinct: try the unfamiliar tool, inspect the data, trace the failure, put a small improvement in front of a user, and learn from what happens. Hardware or connected-device experience can be a strong signal of that mindset, but it is not required. The central work is building dependable software for an operation that changes throughout the day.

As an Engineering Lead, Clinical Operations, you will

• Work directly with supervisors, clinical field staff, and operations leaders to understand schedules, travel, capacity, handoffs, and the exceptions that disrupt a day’s work.
• Build field visibility and intervention tools that give supervisors useful context, distinguish current facts from missing information, and help them respond to changing conditions.
• Develop scheduling and dispatch capabilities that match people and visits to practical constraints, with clear ways for operating staff to review and adjust the plan.
• Build and debug APIs, mobile workflows, integrations, and data flows supporting field teams, connected equipment, and home technology.
• Prototype quickly and ship focused increments. Make deliberate choices about what to build, integrate, or buy, and avoid committing to a large system before the operation has tested the approach.
• Use AI actively for development, investigation, prototypes, analysis, and useful workflow capabilities. Check the behavior and make failures understandable and recoverable.
• Coach engineers and take on a small number of direct reports as the team develops. Maintain clear ownership, sound engineering practices, and credible delivery commitments.
• Partner with Product, Special Project Leads, IT, Counterpart, and the Engagement lead at the interfaces their work shares with field operations.

Success in this role looks like

• First 90 days: You understand how the field operation works, have shipped an improvement used by supervisors or field staff, and can show what it changed. You have a focused technical plan grounded in real constraints and exceptions.
• First six months: Several useful increments are in place. Supervisors can understand and respond to disruptions more effectively, scheduling and field workflows are improving, and technical ownership is clear.

You should get in touch if

• You are a strong production software engineer who has owned meaningful work end-to-end and still builds regularly.
• You can move across backend services, APIs, data flows, user interfaces, and operational workflows to solve a real problem.
• You have strong product instincts, learn unfamiliar domains directly, and enjoy working with the people using what you build.
• You have an iterative, curious approach to technology. You can describe an unfamiliar system you explored, a practical prototype you tried, or a failure you traced across boundaries.
• You use AI in your own engineering work and have practical experience building or integrating AI-backed capabilities, with clear verification and evaluation.
• You can coach engineers and are interested in responsibility for a small team as it develops. Formal management experience can help, but a strong record of Engineering Leadership and coaching also matters.