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Senior Software Engineer – Backend / Systems / AI

Location: San Francisco, CA
Employment Type: Full-Time
Work Arrangement: On-Site, 5 Days per Week
Base Salary: 190,000–250,000
Equity: 0.1%–0.5%, based on seniority

About the Opportunity

We are partnering with a fast-growing healthcare technology company building an AI-powered platform to modernize complex operational workflows for large healthcare enterprises.

The company is addressing a significant challenge in healthcare: fragmented systems, manual processes, and operational inefficiencies across scheduling, billing, insurance, payments, and reporting.

The engineering team builds production systems that automate these workflows, improve reliability, and scale across enterprise customers.

This is an opportunity for a senior- to staff-level backend or systems engineer who wants significant technical ownership, challenging infrastructure problems, and the ability to build and operate AI-powered products in production.

The team operates in a fast-paced, highly collaborative environment where engineers own meaningful projects end to end, from architecture and development through deployment and ongoing operation.

What You'll Do

  • Design and build scalable platform modules supporting complex healthcare operations, including scheduling, patient communication, insurance, accounts payable, reconciliation, credentialing, and reporting.

  • Own products, services, or infrastructure modules from initial design through development, deployment, and production operations.

  • Build reliable, secure systems capable of supporting large enterprise customers and growing operational demands.

  • Work with forward-deployed engineers and customer-facing teams to transform customized solutions into reusable, scalable products.

  • Build and operate AI agents and LLM-powered workflows in production, incorporating evaluations, guardrails, observability, and customer feedback loops.

  • Lead infrastructure projects from initial scoping through rollout, including tools that enable nontechnical teams to configure customer-specific workflows.

  • Design and improve data models, pipelines, and integrations with practice management, billing, payment, and vendor systems, including systems without traditional APIs.

  • Take responsibility for production reliability, troubleshooting, on-call support, and root-cause analysis.

Required Qualifications

Candidates must meet the following requirements to be considered:

  • 4–10 years of full-time software engineering experience, with approximately 6–7 years preferred.

  • Strong backend or systems engineering experience, including production services, infrastructure, system architecture, and scalable applications. Full-stack engineers are welcome if their experience is substantially backend-focused.

  • A demonstrated track record of building, deploying, and maintaining reliable production systems.

  • Experience owning a product, service, or technical module end to end, including scoping, architecture, implementation, deployment, and ongoing operations.

  • Daily, hands-on use of AI coding tools, such as Claude Code or Codex, as part of your engineering workflow.

  • A background that includes at least one of the following:
    • Education at a highly regarded computer science or engineering institution.

    • Professional engineering experience at a high-performing, technically rigorous organization, such as a leading technology company or fast-growing AI startup.

  • Ability to operate independently, make technical decisions, and take ownership of complex engineering challenges with minimal oversight.

  • Ability to work on-site in San Francisco five days per week.

  • Existing U.S. work authorization without the need for visa sponsorship, now or in the future.

Additional Qualifications

The following experience is particularly valuable:

  • Building and shipping AI agents or LLM-powered workflows in production, with a focus on applied engineering rather than model training or research.

  • Engineering experience at a fast-growing startup.

  • Experience with Python, TypeScript, AWS, or Cloudflare.

  • Experience designing infrastructure, integrations, or distributed systems that support demanding production environments.

  • A background in engineering environments emphasizing technical rigor, reliability, scalability, and individual ownership.

Technology Stack

The engineering environment includes:

  • Languages: Python, TypeScript

  • Cloud & Infrastructure: AWS, Cloudflare

  • AI & Automation: AI Agents, LLM-powered workflows

  • Development Tools: Claude Code, Codex

Experience with every technology listed is not required. However, candidates should have a strong backend/systems engineering foundation and already be using AI coding tools in their daily work.

Work Environment

This is a fully in-person engineering position in San Francisco, with the entire engineering team working together on-site five days per week.

The environment is designed for engineers who thrive with autonomy, technical responsibility, and direct collaboration.

Engineers are expected to take ownership of meaningful projects, move quickly, and remain closely involved in the systems they build.

Relocation support may be available for qualified candidates.

Compensation & Benefits

  • Base Salary: 190,000–250,000 annually, depending on experience and seniority.

  • Equity: 0.1%–0.5%, based on seniority, with a four-year vesting schedule and one-year cliff.

  • Health Benefits: Full medical, dental, and vision coverage.

  • Paid Time Off: Unlimited PTO.

  • Meals: Lunch and dinner provided in the office.

  • Relocation: Support may be available for the right candidate.

Visa Sponsorship: Not available. Candidates must already have unrestricted U.S. work authorization that does not require employer sponsorship.

Who Will Thrive in This Role

This opportunity is best suited for a hands-on engineer who has already demonstrated the ability to build and operate complex production systems, enjoys solving difficult technical problems, and wants direct responsibility for the outcomes of their work.

The ideal candidate combines strong backend or systems engineering experience with modern AI-assisted development practices and is motivated by the opportunity to build scalable, real-world technology in a high-ownership environment.

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