We are currently looking for talent to join a fast-growing Czech FinTech environment (non‑bank lender) that is entering a new phase: evolving a fast-moving startup product into a stable, sustainable enterprise platform. The role involves supporting an existing legacy system while helping build a modern, next‑generation solution in parallel – and we’re expanding our team to drive this transition.
Joining this team means working with a modern tech stack, shaping architecture, and influencing how a proven startup grows into a long-term, resilient product. 🚀
As a Python Engineer, you will:
- design product architecture and implement simple and complex features
- suggest improvements across technical and product areas
- help break down epics and provide technical estimates
- work closely with other developers, QA engineers and managers
- work with business consultants to understand and address needs of business
What skills should you have?
- senior-level back-end Python programming with a proven track record of delivering systems to production
- developing clean modules and maintaining high code clarity
- designing and implementing backend services and APIs
- thinking in terms of maintainability, clarity, and long-term evolution of systems
- hands-on experience with MongoDB or similar document databases
- understanding of message queues and event-driven communication patterns
- ability to quickly learn new frameworks, tools, and patterns when needed
- have strong testing culture: write unit (component, integration, and end-to-end tests when applicable) for your features
- using type checking and static analysis as part of daily workflow
- ability to provide thoughtful, constructive code reviews and have commitment to engineering excellence
Additionally it would be great if you:
- have experience in FinTech / lending / payments domain
- have experience with AWS (or GCP, Azure) services and cloud infrastructure
- have solid Docker skills and understanding of containerized environments
- are able to work with CI/CD systems (GitHub, GitLab) and are not afraid to write/setup pipeline yourself
- are comfortable with infrastructure-as-code and automation practices
Tech stack - tools that we currently use or plan to use in the future:
- Python 3.1X, FastAPI, Pydantic, Pytest, Mypy (we’re planning to try 'ty')
- ruff, uv, Docker, AWS (SDK, CDK, CloudFormation, EC2, ECS, Fargate, S3, Dynamo, Kinesis, SQS, AWS Lambda, CloudWatch, SSM)
- OpenTelemetry, Prometheus, Grafana, Ansible, GitLab CI/CD
What we offer:
Meaningful Technical Growth
- deep, hands‐on work with modern Python tooling and cloud technologies
- real ownership of architecture and long‐term technical direction
Build Engineering Culture You Can Be Proud Of
- strong focus on code quality, clarity, and maintainability
- pragmatic decision‐making — no over‐engineering, no unnecessary bureaucracy
- a team that is actively shifting toward thoughtful engineering over rushing features
High Impact on the Product
- direct influence on architectural decisions and system evolution
- close collaboration with product and business teams
Flexible, Modern Work Environment
- fully remote work setup with flexible working hours with the ability to collaborate during CET
business hours
- async‐friendly communication that supports deep work
- international team with diverse perspectives and experience
Compensation & Benefits
- competitive salary and yearly bonuses
- paid time off and sick-days
This role may not be a good match if:
- you need close guidance, step‐by‐step direction, or struggle to self‐organize your work
- ambiguous requirements frustrate you, or you prefer others to fully define solutions before you start
- writing tests feels like overhead, or you tend to ship features without strong test coverage
- you resist code reviews or see them as a formality rather than a collaborative quality practice
- cloud infrastructure makes you uncomfortable, or you avoid DevOps‐related tasks even when they’re simple
- async communication feels slow or difficult, and you rely heavily on synchronous discussions to move forward
- you prefer sticking to familiar tools and patterns rather than learning new ones when the situation calls for it
- you avoid ownership, or you tend to over‐engineer or under‐engineer solutions instead of aiming for pragmatic clarity
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