Middle+/Senior Software Engineer (Python)

Описание вакансии

A Stealth-mode AI-powered Cloud-Native Health-Tech is looking for a Middle+/Senior Software Engineer (Python).

The Business Domain revolves around providing Better Care for the US Patients; meaning, it’s about Treating Patients well. The company was founded more than five years ago. It’s not vaporware, their platform supports US Physician Networks (IPAs) by enabling Smarter, Risk-Adjusted, and more Predictive Care that improves real patient outcomes.

Compensation and Benefits:

Paid Time Off

The company has Unlimited PTOs Policy and compensated New Years Holidays on top of that. The misuse of the policy isn’t welcomed, though it’s definitely possible to take at least two weeks – and fully compensated – vacation, or more.

Corporate Hardware

The company provides Corporate Hardware for employees who completed their Probationary Period, as well as proven their value.

Location and timezone

We are focused on hiring in time zones overlapping with the US or Western Europe. Also considering additional locations where time zone overlap and payroll compliance can be reliably supported, including certain Eastern European and Middle Eastern countries (Bulgaria, UAE, etc.).

Target Stack:

Necessary: Python (FastAPI, pytest); Cloud Spanner; Google Kubernetes Engine (GKE); Pub/Sub; Git (GitHub, GitFlow);

As a plus: Google Cloud Platform (GCP); LLMs and GenAI; BigQuery; Cloud Composer (Airflow, DBT); Google Cloud Build; GSuite; Terraform; SonarSource; LucidChart.

NOTE: Similar Cloud-Native Experience is always an option.

NOTE: Knowledge of any OLTP Database (instead of Cloud Spanner) is always an option.

Overview of Future Responsibilities:

Proactive Studying and desire to grow.

Working Diligently and desire to bring value.

Software & Agentic AI Engineering. Design, develop, and implement autonomous AI workflows, LLM integrations, and robust backend software solutions.

Software Engineering (including writing Auto Tests) using Python; Future possibility to learn Go.

Infrastructure Optimization. Continuously improve and optimize Data Infrastructure, ensuring high performance, scalability, and security by utilizing Cloud Composer, BigQuery, and other bits of the Modern Data Stack.

Working in a TDD-like environment that implies driving Development from Tests. Both tests and code already support through and through breakpoints, while the Interpreter itself is fully containerized.

Separation of Development and Operations.

Learning Data Engineering and Data Analytics in the future.

Requred experience:

5+ years of hands-on experience working as a Software Engineer; preferably, with a focus on cloud-native backend development and building Agentic AI systems.

Practical experience integrating LLMs, developing autonomous agents, and utilizing AI to solve complex business problems.

Advanced Knowledge of Python for Software Development, AI integrations, and Automation.

Strong grasp of OOP, including OOP Pitfalls and Patterns.

Advanced Knowledge of SQL, including familiarity with Query Optimizations.

3-5+ years of hands-on Experience with OLTP Databases, where Cloud Spanner is always preferred.

Cloud & Infrastructure

Experience with Google Cloud Platform (or similar cloud exp.)

Familiarity with Cloud Composer (Airflow-based orchestration).

Basic understanding of Docker.

Experience working in a Unix-like development environment (macOS or Linux).

Fundamentals

Deep knowledge of Mathematics, Statistics, Algorithms and Data Structures, etc, is always prioritized. Actually, Software Engineering — unlike Web Development — implies at least superficial knowledge of Algorithms and Data Structures.

Ability to work in an Iterative Development workflow. This role involves evolving solutions through Incremental Delivery rather than a Waterfall-style approach.

There are many other Experience Advantages a candidate may have, e.g., Kafka, Apache Beam (Dataflow) Streaming, Spark Streaming, Python’s asyncio, Terraform, etc.

Target Workflow

Cloud-Native (GCP) is always prioritized higher than self-hosted, on-premise, or homemade over Virtual Machines solutions. There are exceptions, such as we’re keenly trying to avoid Fully Serverless (Cloud Functions or Cloud Run over Pub/Sub or GCS) solutions.

The focus is on writing Pythonic Solutions and Style Guide-compliant SQL. SonarSource software is a ready-to-use helper. It’s definitely possible to write some bits in Go, where this PL is really applicable, though the default PL is Python.

Lakehouse-first Data Engineering (BigQuery, Cloud Composer, DBT) and Decoupled Distributed Data Processing are always prioritized higher than running Imperative Solutions over GKE or than doing Coupled Massively Parallel Processing Compute.

Imperative Code Solutions – including Classical Algorithms and Data Structures –, implemented over Dataflow or Spark are expected to come up only when the Lakehouse-first Approach isn’t applicable or is too costly.

Компания, занимающаяся разработкой облачных технологий для здравоохранения на базе искусственного интеллекта, ищет Middle+/Senior Python инженера для долгосрочного сотрудничества. Это не виртуальный продукт: их платформа поддерживает сети врачей (IPA), обеспечивая более интеллектуальное, адаптированное к рискам и прогнозируемое лечение, которое улучшает реальные результаты лечения пациентов.

Вы присоединитесь к международной команде первоклассных профессионалов, которые с энтузиазмом создают продукты, улучшающие качество медицинских услуг.

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