Senior Full-Stack Engineer (AI-Augmented Systems)

We are a healthcare tech start up and we are looking for a Senior Full-Stack Engineer (AI-Augmented Systems)

We are building the digital front door for healthcare access.

Lab Online Booking (LOB) is already operating at real-world scale:

• Millions of appointments processed
• Deployed across multiple health organizations
• Core infrastructure for patient access and flow

We are expanding into:

• imaging
• immunization
• full patient journey orchestration

We are looking for engineers who can build systems, not just features, and who use AI to multiply their output.

What You’ll DoBuild Core Platform Systems

• Design and develop scalable scheduling and patient flow systems
• Build APIs and services for:
• appointment booking
• queue management
• real-time updates
• Ensure reliability in high-volume, multi-site environments

Own End-to-End Development

• Take features from concept → production
• Work across:
• backend (APIs, databases, integrations)
• frontend (patient and admin interfaces)
• Ship fast and iterate continuously

Integrate with Healthcare Systems

• Work with EMR / LIS environments
• Build lightweight integrations (HL7 / FHIR where applicable)
• Maintain minimal PHI architecture

AI-Augmented Engineering (Non-Negotiable)

You are expected to:

• Use AI tools to 2–5x your productivity
• Generate, debug, and refactor code using AI
• Automate repetitive tasks and accelerate development cycles

Examples:

• ChatGPT / Claude for architecture and coding
• Copilot / Cursor for development workflows
• AI-assisted debugging, testing, and prototyping

Think in Systems, Not Tickets

• Design for the full patient journey:

booking → arrival → check-in → completion

• Handle real-world constraints:
• walk-ins vs appointments
• multi-site coordination
• edge cases and concurrency

RequirementsMust-Have

• 5+ years full-stack development experience
• Strong backend experience (Node.js, Python, or similar)
• Frontend experience (React or similar)
• Experience building scalable, production systems

Critical (Non-Negotiable)

• AI-native workflow
• You actively use AI to increase speed and quality
• You can clearly demonstrate how AI improves your output

Strong Advantage

• Healthcare systems experience (EMR, scheduling, workflows)
• Experience with real-time systems or queueing systems
• Experience with SRED
• Familiarity with HL7 / FHIR
• DevOps / cloud experience (AWS, GCP, DigitalOcean)

What Success Looks Like

• Features ship in days, not weeks
• Systems remain stable under real-world load
• Patient and staff experiences are fast, clear, and reliable
• Engineering output is significantly amplified through AI

Compensation

This role is structured as a high-leverage, part-time engagement focused on building critical platform systems.

Initial Structure

• 10–20 hours per week (flexible)
• Compensation: hourly or project-based, aligned with experience and output
• Typical range: $40–$120/hour depending on seniority and capability

Output-Driven Model

Compensation is tied to impact, not time.

Examples of high-value deliverables:

• Scheduling engine improvements
• Real-time queue system deployment
• System integrations (EMR / LIS)
• Performance and scalability enhancements

Engineers who produce high-impact results will receive:

• increased scope
• higher compensation
• priority for long-term roles

Growth & Upside

Top performers will have the opportunity to:

• Transition into a full-time senior or lead engineering role
• Own core system architecture
• Participate in equity / long-term upside

Why This Role is Different

• You are building infrastructure used in real healthcare environments
• You will solve high-volume, real-world system problems
• You are expected to operate with speed, ownership, and leverage
• AI is a core part of how we build—not an add-on

How to Apply

Send:

• GitHub or portfolio (real systems, not tutorials)
• Description of systems you’ve built (scale, complexity)
• Explanation of how you use AI in your development workflow

Job Types: Full-time, Part-time

Pay: $35.00-$120.00 per hour

Expected hours: 10 – 20 per week

Work Location: In person