We’re looking for a Backend Tech Lead (Python) to join a fast-moving team that’s revolutionizing digital healthcare through AI. You’ll lead backend development and architectural decisions for an advanced platform that integrates with EHR systems, reducing administrative load for clinicians and improving patient outcomes.
In this role, you’ll drive technical leadership, own microservices architecture, and collaborate with cross-functional teams to ensure our large-scale AI infrastructure is scalable, reliable, and cloud-optimized.
Responsibilities
- Lead the design and development of backend systems using Python and FastAPI
- Architect and scale a microservices-based infrastructure on AWS with Kubernetes
- Collaborate with Data Scientists and AI Engineers to integrate ML models into production
- Optimize databases and backend performance for high-throughput, real-time applications
- Guide architectural decisions, conduct code reviews, and mentor team members
- Take ownership of backend deliverables from planning to production
Requirements
- 8+ years of experience in backend development with Python
- Proven experience with AWS, Kubernetes, and FastAPI
- Profound understanding of microservices architecture and distributed systems
- Strong grasp of system design, OOP principles, and performance optimization
- Experience with cloud-native infrastructure and CI/CD pipelines
- Excellent communication and leadership skills
- Bachelor’s or Master’s degree in Computer Science or a related field
Will be a plus
- Background in healthTech or AI-powered platforms
- Familiarity with EHR systems or clinical data workflows
- Experience scaling backend systems for data-intensive applications
What we offer
- Competitive salary and benefits package
- Medical insurance
- Hybrid set of works
- Collaborative and innovative work environment
- Career growth and development opportunities
- A chance to work with a talented and driven team of professional
About the project
Our client is reshaping digital healthcare with a cutting-edge AI platform that integrates directly into Electronic Health Record (EHR) systems. The solution automates core clinical workflows: prescription refills, lab result reviews, patient messages by surfacing relevant data and suggested actions in real time.
It leverages ML models trained on tens of millions of medical cases to optimize decision support and minimize manual input. The system is engineered for seamless interoperability, ensuring minimal disruption to clinical environments. Backed by $25M in funding, the team is composed of engineers with backgrounds in AI, data infrastructure, and healthTech scalability.
