We are looking for a Senior Python Backend Engineer who is passionate about applying modern AI-assisted software development practices to build secure, scalable healthcare platforms.

Beyond strong backend engineering skills, we are looking for someone who actively leverages AI development tools, LLM-powered workflows, and automation to improve engineering productivity, code quality, and delivery speed.

You will work on a modern healthcare interoperability platform while collaborating with an engineering team embracing AI-first development practices and cloud-native technologies.

The platform enables secure access, exchange, and processing of clinical healthcare data across providers, healthcare organizations, and patients using modern interoperability standards including FHIR.

The engineering team embraces AI-assisted software development, modern cloud-native architecture, and automation-first engineering practices. Engineers are encouraged to use AI tools to improve software quality, accelerate development, automate repetitive tasks, and increase engineering productivity.

You will contribute to backend services powering healthcare interoperability while helping evolve the team's AI-native engineering practices.

Requirements

- 5+ years of professional software engineering experience developing backend applications in production environments.
- Strong proficiency in Python (3.11/3.12+) and modern backend development practices.
- Hands-on experience building high-performance asynchronous applications using FastAPI and Python async/await.
- Solid understanding of RESTful API design, distributed systems, and microservice architecture.




- Experience working with MongoDB in production environments; familiarity with Beanie ODM or similar asynchronous ODM frameworks.
- Strong knowledge of authentication and authorization technologies, including OAuth 2.0, OpenID Connect (OIDC), JWT, and modern Identity Providers.
- Experience developing, debugging, and deploying containerized applications using Docker and Docker Compose.
- Strong understanding of software architecture, scalability, reliability, and performance optimization.
- Experience writing automated tests using Pytest and applying modern software quality practices.
- Familiarity with CI/CD pipelines and modern DevOps workflows.
- Strong analytical, troubleshooting, and debugging skills.
- Excellent communication skills and ability to collaborate effectively within cross-functional Agile teams.
- Proven experience using AI-assisted software development tools to improve engineering productivity, software quality, and development velocity.
- Hands-on experience with one or more AI coding assistants such as GitHub Copilot, Cursor, Claude Code, ChatGPT, Windsurf, or similar.
- Ability to effectively leverage Large Language Models (LLMs) for code generation, debugging, refactoring, documentation, test generation, and architectural exploration while maintaining high engineering standards.
- Experience reviewing, validating,



and improving AI-generated code with strong engineering judgment.
- Experience developing healthcare interoperability solutions or working within Digital Health platforms.

Nice to have

- Knowledge of healthcare interoperability standards, including:
- HL7 FHIR R4
- SMART Health Links (SHL)
- SMART Health Cards (SHC)

- Experience building secure clinical data exchange pipelines and healthcare integration workflows.
- Familiarity with JWE encryption/decryption mechanisms and secure healthcare data transmission.
- Experience with Model Context Protocol (MCP) and AI integration frameworks.
- Experience developing MCP servers or AI-enabled backend services.
- Experience integrating Large Language Models (LLMs) or AI services into enterprise applications.
- Knowledge of Retrieval-Augmented Generation (RAG), AI agents, or agentic application architectures.
- Experience integrating with external platforms and services, including:

- Google Drive
- Microsoft OneDrive
- Box
- SMTP services
- FHIR servers

- Familiarity with QR code and image decoding technologies (e.g., pyzbar, zbar).
- Experience with Playwright-based end-to-end testing frameworks.
- Knowledge of Cucumber/BDD methodologies.
- Experience with observability and monitoring technologies, including:

- OpenTelemetry

- Experience working with event-driven architectures and Kafka.
- Experience with AWS cloud services, including AWS Secrets Manager.
- Exposure to TypeScript and React for occasional full-stack contributions.
- Experience working in regulated industries requiring strong security, privacy, and

📌 Senior Python Backend Engineer (Colombia)
🏢 Intellias
📍 Colombia