About the Company

Verto Health is a health technology company solving healthcare’s most complex data fragmentation and interoperability challenges. Our patented, AI-enabled platform ingests structured and unstructured clinical data across disparate EHRs, claims, and payer systems to create a unified, actionable view of patient populations. We empower health systems and value-based care organizations across North America to master population health by translating hidden clinical insights into personalized patient journeys, automated workflows, and accurate risk adjustments. By bridging the gap between raw data and coordinated action, Verto enables healthcare providers to reduce manual overhead, optimize operational efficiency, and deliver proactive, data-driven care at scale.

The Role

As a Senior Full-Stack Developer at Verto, you are one of our most senior individual contributors and a technical leader others look to for guidance. You lead through technical excellence, setting engineering standards by delivering high-quality, scalable solutions from design to production. You drive architectural decisions, tackle complex technical challenges, and consistently ship clean, maintainable, production-ready code every sprint.

Management relies on you to turn strategy into execution. You own our AI development harness, the tools, prompts, agents, and workflows that engineers and non-technical partners use to accelerate the SDLC. You treat generative AI as core infrastructure, tuning and extending it to raise the team's output. Working across our platform, its AI pipelines, and complex data, you directly shape what we build and ship. This role will report to the Senior Engineering Manager, Software.

What to Expect

Technical Ownership & Architecture

• End-to-end delivery: Lead the design and build of complex, full-stack features across the stack, with clean, scalable, well-tested code, high coverage, and stable deployments.
• Own the architecture: Co-lead the Architecture Review Board (ARB), set system boundaries and design standards, make the critical calls on data access patterns and service design, and keep the systems you own reliable and well-instrumented.
• Set the technical direction: Own the platform's multi-quarter technical vision and its foundational system design, set the technical roadmap alongside leadership, and take accountability for the hardest problems.
• Development process optimization: Use the sprint buffer to research better methodologies, refactor legacy components, and reduce architectural friction;

Team & Delivery Leadership

•  Translate strategy into execution: Turn high-level technical strategy into scoped, estimated, sequenced work the team can ship predictably.
• Delivery partner: Surface risk early and clearly, and drive shared delivery timelines with enterprise clients. May need to interface with external clients and partners for delivery.
• Hiring and onboarding: Support the Senior Engineering Manager with hiring by running technical and panel interviews, and take ownership of onboarding new developers and co-ops.

AI Development Harness

• Own the harness: Own and continuously improve the internal AI harness that speeds up the whole SDLC.
• Set the example: Use the AI harness heavily in your own work and help the rest of the team get more out of it.
• Enable non-technical partners: Build guard-railed AI workflows that let Product and Project Managers safely contribute to full-stack development and functional reviews.

Mentorship & Code Quality

• Code review: Run rigorous code and design reviews across the pod.
• Standards: Enforce security, architecture, and error-handling standards for all work that ships.
• Mentorship: Act as the primary technical escalation point for junior and intermediate developers, and grow them through hands-on guidance.
• Scoping: Break broad business requirements into digestible stories with clear, defensible estimates.

Domain & Integration Execution

• Systems integration: Build and maintain high-performance endpoints and synchronization pipelines that connect our platform with external systems and data sources (e.g. EMRs and health-system databases).
• Applied domain work: Apply domain knowledge to complex modules such as Risk Adjustment (RAF/HCC), quality metrics, and population dashboards. Deep healthcare experience is an asset here rather than a requirement.

How Success Is Measured

• Predictable delivery: Features ship within committed estimates, and rework and defect rates trend down over time.
• Architecture health: Systems you own meet their reliability and performance targets, and technical-debt paydown stays on schedule.
• AI adoption: The AI Development harness you maintain produces measurable gains in team throughput and cycle time.
• Team and trust: Developers and co-ops you onboard ramp faster and take on harder work, and leadership routinely hands you ambiguous, high-stakes problems knowing they will be handled.

Who You Are

Education & Certification

• Bachelor's degree or higher in Computer Science, Engineering, or a related technical field.

Knowledge & Experience

• Technical mastery: 4+ years writing production-level code, with deep proficiency in our core stack (Python, Ruby, JavaScript/TypeScript, with Go a plus) and modern frameworks (Rails, Flask, React, Vue.js, Angular), plus a track record of designing scalable, reliable systems and owning them in production.
• Infrastructure & DevOps: Strong hands-on experience with containerization (Docker, Kubernetes), CI/CD pipelines, and cloud services (Azure, AWS, or GCP).
• Database architecture: Advanced experience querying and optimizing databases of different formats (PostgreSQL, Clickhouse, Elasticsearch, Redis).
• AI tooling: Active daily user of AI development tools (Cursor, Claude, Codex, Gemini, etc.), with experience building or extending AI-augmented development workflows.

Relevant Skills

• Autonomy and delivery: Self-manage complex work, ask sharp questions to solve the right problem, and consistently deliver within sprint estimates.
• Sound judgment: Earns respect as a technical leader and is trusted with ambiguous, high-stakes decisions under pressure.
• Communication: Explain technical trade-offs clearly to both engineers and non-technical stakeholders.
• Healthcare domain (an asset): Familiarity with EMR data structures, unstructured clinical notes, and interoperability standards (HL7v2, FHIR, CCLF) is a plus, not a requirement.

Why Verto

• Opportunity to see your code deployed in hospitals and clinics across Canada
• Work with a cross-functional team of healthcare professionals and technologists
• Generous professional development support and flexible work options
• Optional hybrid team with strong culture of collaboration and growth

Compensation

The salary range for this role is $140,000 to $175,000 CAD per year, depending on experience, skills, and alignment with the role.

In addition to base compensation, Verto Health offers a comprehensive benefits package, which may include health and dental coverage, paid time off, professional development support, and flexible work arrangements.

Compensation is reviewed regularly to ensure fairness, market alignment, and internal equity.

Ready to Apply

At Verto Health, whether you’re just starting out or ready to lead large-scale initiatives, you’ll find a place here to grow, collaborate, and make real-world impact.

Do you have 70% of the qualifications we’re looking for? That’s enough. Apply anyway.

Verto Health is committed to providing an inclusive and accessible experience for all applicants. If you require accommodations during the recruitment process, please let us know and we’ll work with you to meet your needs.

Use of AI in the Hiring Process

Verto Health uses artificial intelligence-enabled tools during the recruitment process to assist in screening, assessing, and selecting applicants for this position. This includes tools to evaluate candidate skills, experience, and qualifications against the role requirements.

AI tools are used to assist our hiring team, not to make final hiring decisions. All candidate applications and interview outcomes are reviewed and evaluated by people. If you have questions about how AI is used in our hiring process, please reach out.