Backend Engineer

We're seeking a Backend Engineer to join our core team as we build technology that transforms behavioural health care. As one of our early engineering hires, you'll have an outsized impact on our technical architecture, product direction, and company culture. You'll be responsible for designing and implementing scalable backend systems that process sensitive healthcare data, working with distributed architectures that support real-time patient interactions, and contributing to AI-driven clinical tools that directly impact patient outcomes. This is a unique opportunity to shape the technical foundation of a company that's revolutionising mental health care, with significant equity upside and the autonomy to make architectural decisions that will scale with our growth.

Responsibilities:

• Architect and develop core backend services using Spring Boot that power our AI-driven platform.
• Design and implement comprehensive monitoring, alerting, and observability infrastructure using Prometheus and Grafana.
• Configure and manage AWS scaling policies to ensure system reliability and cost optimisation.
• Build distributed systems leveraging message queues and streaming platforms (SQS, Kafka, Kinesis) for high-volume asynchronous workloads.
• Implement robust data reliability strategies including redundancy, failure handling, and disaster recovery.
• Design and optimise LLM integration pipelines, including prompt engineering, usage monitoring, and quality assurance.
• Establish security best practices using Spring Security, implement RBAC, and ensure HIPAA compliance.
• Model and optimise complex clinical and operational workflows, translating domain requirements into well-structured, maintainable backend processes.
• Make foundational technical decisions that will scale as we grow from startup to industry leader.
• Collaborate directly with founders and clinical teams to translate healthcare needs into scalable technical solutions.
• Own major product features end-to-end, from architecture to deployment.

Requirements:

• Systems Thinker: You naturally reason about distributed systems, failure modes, and data consistency. You design for what goes wrong, not just what goes right.
• Reliability-Focused: You believe monitoring and alerting aren't afterthoughts; they're core engineering deliverables. You sleep better when dashboards are green, and alerts are actionable.
• Problem Solver: You are resourceful and can architect smart solutions when faced with complex, non-standard requirements or scaling challenges.
• Ownership Mindset: You are happy to roll up your sleeves to handle both high-level architecture decisions and the critical operational details that keep a production system running.

Required Qualifications:

• 5+ years of software engineering experience.
• Deep expertise in the Spring Boot framework and Java ecosystem for building production-grade applications.
• Proficiency in monitoring and observability tools, specifically Prometheus and Grafana for creating dashboards and alerts.
• Strong experience with AWS services including provisioning and managing auto-scaling policies, EC2 ECS/EKS.
• Proven expertise in architecting scalable distributed systems using message queues and streaming platforms (SQS, Kafka, Kinesis).
• Experience implementing data reliability patterns including redundancy, circuit breakers, retry mechanisms, and graceful failure handling.
• Hands-on experience with LLM technologies including prompt engineering, usage monitoring, and quality metrics.
• Strong security engineering background with Spring Security, implementing RBAC, and healthcare compliance standards.
• Experience with process modelling and translating complex domain workflows into backend logic.
• Demonstrated ability to build systems that handle asynchronous workloads at scale.
• Experience with event-driven architectures and microservices patterns.
• Ability to thrive in a fast-paced startup environment.
• Excellent communication and collaboration abilities.

Bonus Points:

• Experience in audio/signal processing.
• Domain-Driven Design (DDD) experience and principles.
• Advanced Confluent Kafka platform expertise.
• Infrastructure as Code experience with Terraform.
• Experience with additional cloud platforms (GCP, Azure).
• Background in real-time systems or media processing.
• Healthcare technology or HIPAA compliance experience.
• Experience with AI/ML model deployment and monitoring.
• Open-source contributions.