Senior Software Engineer, AI Builder (Python) - Datarails

End-to-end ownership: Own features from requirements and technical design through implementation, testing, deployment, and production monitoring. AI-native development: Use AI coding agents as a core part of your daily workflow across development, testing, debugging, documentation, and automation. Engineering judgment: Review, challenge, and validate AI-generated solutions, making sure what gets shipped is correct, secure, scalable, and maintainable. Product partnership: Product owns the what, you own the how. Work closely with Product to understand the problem, challenge assumptions, evaluate trade-offs, and find pragmatic technical solutions. Broad technical ownership: Strong software engineering fundamentals and solid understanding of architecture and design principles. Python and Django will be the primary technologies, but you will take responsibility for whatever is required to deliver a feature, including frontend, QA, automation, infrastructure, and integrations Outcome focused: Success is measured by the quality and impact of what you ship, not by the amount of code you write. Own product features end-to-end, from requirements through production and monitoring. Work with Product to translate business problems into clear technical solutions and execution plans. Design scalable and maintainable solutions, including architecture, APIs, data models, and integrations. Use AI coding agents to accelerate implementation, testing, debugging, and automation. Review and improve AI-generated code, ensuring high standards for correctness, security, performance, and maintainability. Make independent technical decisions and communicate architectural trade-offs clearly. Contribute across backend, frontend, QA, CI/CD, and infrastructure when needed to deliver a feature. Investigate and solve complex production and performance issues. Continuously improve how we build, test, and ship software using AI-native development practices. BSc in Computer Science or equivalent experience. 7+ years of experience building and shipping production software, with a strong track record of owning features or systems end-to-end. Strong system design fundamentals and experience building scalable SaaS systems in the cloud. Ability to make sound architectural decisions independently and understand technical trade-offs. Solid understanding of REST APIs, asynchronous programming, distributed systems, microservices, and testing. Hands-on experience with AI coding tools such as Claude Code, Cursor, Codex, GitHub Copilot, or similar. Strong ability to review, challenge, and improve AI-generated code rather than relying on it blindly. Strong product mindset, with the ability to balance technical and business priorities and focus on solving the underlying problem. Strong ownership mentality and ability to drive work independently from idea to production. Excellent communication skills and high proficiency in English, with the ability to work directly with Product and engineering teams. Experience with modern frontend technologies, particularly Angular. Experience with CI/CD pipelines and infrastructure-as-code tools such as Terraform or Helm. Familiarity with Celery, RabbitMQ, event-driven architectures, or streaming systems. Experience with cloud infrastructure, Docker, and Kubernetes. Experience with QA automation and end-to-end testing.

Own product features end-to-end, from requirements through production and monitoring. Work with Product to translate business problems into clear technical solutions and execution plans. Design scalable and maintainable solutions, including architecture, APIs, data models, and integrations. Use AI coding agents to accelerate implementation, testing, debugging, and automation. Review and improve AI-generated code, ensuring high standards for correctness, security, performance, and maintainability. Make independent technical decisions and communicate architectural trade-offs clearly. Contribute across backend, frontend, QA, CI/CD, and infrastructure when needed to deliver a feature. Investigate and solve complex production and performance issues. Continuously improve how we build, test, and ship software using AI-native development practices.

End-to-end ownership: Own features from requirements and technical design through implementation, testing, deployment, and production monitoring. AI-native development: Use AI coding agents as a core part of your daily workflow across development, testing, debugging, documentation, and automation. Engineering judgment: Review, challenge, and validate AI-generated solutions, making sure what gets shipped is correct, secure, scalable, and maintainable. Product partnership: Product owns the what, you own the how. Work closely with Product to understand the problem, challenge assumptions, evaluate trade-offs, and find pragmatic technical solutions. Broad technical ownership: Strong software engineering fundamentals and solid understanding of architecture and design principles. Python and Django will be the primary technologies, but you will take responsibility for whatever is required to deliver a feature, including frontend, QA, automation, infrastructure, and integrations Outcome focused: Success is measured by the quality and impact of what you ship, not by the amount of code you write. Own product features end-to-end, from requirements through production and monitoring. Work with Product to translate business problems into clear technical solutions and execution plans. Design scalable and maintainable solutions, including architecture, APIs, data models, and integrations. Use AI coding agents to accelerate implementation, testing, debugging, and automation. Review and improve AI-generated code, ensuring high standards for correctness, security, performance, and maintainability. Make independent technical decisions and communicate architectural trade-offs clearly. Contribute across backend, frontend, QA, CI/CD, and infrastructure when needed to deliver a feature. Investigate and solve complex production and performance issues. Continuously improve how we build, test, and ship software using AI-native development practices. BSc in Computer Science or equivalent experience. 7+ years of experience building and shipping production software, with a strong track record of owning features or systems end-to-end. Strong system design fundamentals and experience building scalable SaaS systems in the cloud. Ability to make sound architectural decisions independently and understand technical trade-offs. Solid understanding of REST APIs, asynchronous programming, distributed systems, microservices, and testing. Hands-on experience with AI coding tools such as Claude Code, Cursor, Codex, GitHub Copilot, or similar. Strong ability to review, challenge, and improve AI-generated code rather than relying on it blindly. Strong product mindset, with the ability to balance technical and business priorities and focus on solving the underlying problem. Strong ownership mentality and ability to drive work independently from idea to production. Excellent communication skills and high proficiency in English, with the ability to work directly with Product and engineering teams. Experience with modern frontend technologies, particularly Angular. Experience with CI/CD pipelines and infrastructure-as-code tools such as Terraform or Helm. Familiarity with Celery, RabbitMQ, event-driven architectures, or streaming systems. Experience with cloud infrastructure, Docker, and Kubernetes. Experience with QA automation and end-to-end testing.