Senior Backend Engineer - AI-Powered MedTech (Remote)

Das ist der Job

This position is based in South Africa.

Darum lohnt es sich

With headquarters in London, engineering operations in California, and a new engineering team being established in South Africa, our global team is united by a mission to make cardiovascular care and education smarter, safer, and more effective through intelligent technologies.

The role We're looking for an experienced senior backend engineer to join our team and help us scale an AI‑powered medical education platform. You'll work closely with cross‑functional teams to ship features and keep the platform running reliably at scale. Some international travel may be required for team meetings or project collaboration.

Ownership and collaboration • Take ownership of backend architecture and scaling within your domain. • Work closely with technical leads, AI and frontend engineers on system design and integration. • Collaborate with product, clinical and regulatory teams to ensure backend systems meet user and compliance needs. • Own CI/CD pipelines, deployment processes and production monitoring. • Document systems, processes and architecture for the team.

Benefits • Remote‑first culture with global impact. • Cutting‑edge technology in a meaningful mission. • Healthcare innovation that directly improves patient outcomes. • A collaborative environment with medical device experts.

Cerebria is at the forefront of AI-driven healthcare innovation, developing advanced machine learning solutions that enhance patient safety and improve cardiovascular diagnostics. Our core technology focuses on real-time coronary physiology, supporting interventional cardiologists with intelligent insights during procedures.

In parallel, we are building cutting‑edge education tools that leverage generative AI to deliver personalized, scalable learning experiences for healthcare professionals and patients. Founded by practicing cardiologists, we're a small but growing startup backed by deep expertise in medical devices, regulatory compliance, and systems integration.

From AI model development to seamless deployment in clinical and educational environments, we deliver end‑to‑end innovation. This is a senior, hands‑on role with real technical depth: you'll design APIs, tune databases, manage vector search, and build infrastructure that balances performance with cost efficiency.

We care more about demonstrable depth and a strong production track record than about job titles, so we look for engineers who have genuinely built and scaled backend systems in production.

What you'll do Core backend development • Design, build and maintain high‑performance RESTful APIs with FastAPI. • Architect efficient PostgreSQL schemas and optimise performance at scale. • Manage vector similarity search for AI‑driven content matching. • Integrate LLM provider APIs and self‑hosted models with smart rate limiting, error handling and cost management. • Develop backend systems that are secure and safe by design: apply secure coding, threat modelling and vulnerability management, and build the validation and traceability that healthcare systems in a regulated clinical environment require.

Performance and scaling • Scale databases using connection pooling, query optimisation, partitioning and replicas. • Improve API performance through caching layers, async processing and optimised response handling. • Design cloud infrastructure with auto‑scaling, monitoring and alerting. • Balance performance and reliability with cost optimisation strategies.

What we're looking for The bar is demonstrable depth and a real production track record.

We're looking for engineers who have genuinely built, shipped and scaled backend systems in production and can show it. • Substantial production experience building backend systems in Python, at a level where you've owned real systems rather than only contributed to them. • Proven track record with async frameworks (FastAPI, Django Channels, Flask with asyncio, or similar). • Advanced SQL: query optimisation, indexing and performance tuning (PostgreSQL preferred). • Demonstrable experience with production database management: migrations, connection pooling, backup and recovery. • Hands‑on experience with cloud infrastructure (AWS). • Experience with vector databases or search systems.

Technical skills • Databases: PostgreSQL/MySQL, Redis or similar caching, schema design. • DevOps & Automation: Docker, Kubernetes (or equivalent orchestration), Infrastructure as Code (IaC), automated CI/CD pipelines, deployment automation and configuration management. • Testing: unit, integration and load testing. • Observability tools (Prometheus, Grafana, DataDog, CloudWatch, etc.). • Security: auth, encryption, compliance (GDPR, SOC 2), and secure development practices (OWASP, SAST/DAST, dependency scanning).

Nice to have • Experience with LLM integrations or self‑hosted model deployments. • Background in EdTech or platforms with user‑generated content. • Experience with multi‑tenant systems and data isolation strategies. • Prior work on performance‑heavy, low‑latency applications.