Senior Software Engineer, Python

ComboCurve is an industry leading cloud-based software solution for A&D, reservoir management, and forecasting in the energy sector. Our platform empowers professionals to evaluate assets, optimize workflows, and manage reserves efficiently, all in one integrated environment. By streamlining data integration and enhancing collaboration, we help operators, engineers, and financial teams make informed decisions faster. Trusted by top energy companies, ComboCurve delivers real-time analytics and exceptional user support, with a world‑class customer experience team that responds to inquiries in under 5 minutes. We’re hiring a Senior Software Engineer to join our Platform Team. You’ll help design and build the core services, internal APIs, and data workflows that power ComboCurve’s products. This role is ideal for someone who loves writing modern Python, caring about architecture and testability, and building platform capabilities that make the rest of engineering faster and more reliable. What You’ll Do Build and maintain robust platform services and internal tooling primarily in Python. Design clean, well-typed interfaces and services that scale with growing data volumes and product needs. Develop and own internal APIs that other teams depend on, with strong contracts and documentation. Create high-performance data processing paths inside services to support analytics and ingestion workloads. Deploy and operate Python services on GCP using serverless and managed platforms. Improve CI/CD pipelines, testing practices, and developer experience across the platform. Partner closely with product engineers, data engineers, and leadership to shape platform direction. Write ADRs, architecture diagrams, and technical documentation that scale decision-making. Mentor other engineers through code reviews, pairing, and pragmatic standards-setting. Requirements Advanced Python Proficiency: Deep expertise in Python 3.13+, specifically utilizing type annotations, async/await patterns, and modern language features to build robust platform services. Modern Dependency Management: Hands‑on experience with uv for fast package management (or similar), dependency resolution, and virtual environment handling. Software Architecture Patterns: Strong adherence to SOLID principles and clean architecture; ability to design decoupled, maintainable systems that scale. High-Performance Data Processing: Experience using polars, PyArrow, or Apache Iceberg for efficient large-scale data manipulation and processing within application logic. Data Warehouse Integration: Experience connecting Python applications to modern data platforms like Snowflake or Databricks for data ingestion and retrieval. Google Cloud Platform: Proven track record deploying and managing services on GCP, specifically using Cloud Run, Cloud Functions, and Google Cloud Storage. CI/CD: Ability to design and maintain pipelines for automated testing, linting, and cloud deployment; experience with GitHub Actions is strongly preferred. Automated Testing Strategy: Extensive experience writing comprehensive test suites using pytest, including the use of fixtures, parameterization, and mocking external services. Technical Leadership: Ability to mentor team members through code reviews, ADRs and architecture diagrams. AI Agent Frameworks Experience: building or integrating with AI agent frameworks and LLM orchestration tools to enhance platform automation and capabilities. Shell Scripting: Competency in Bash scripting for automating local developer tasks, build processes, or operational utility scripts. Version Control Mastery: Deep understanding of Git, including branching strategies, conflict resolution, and maintaining a clean commit history. Containerization: Proficiency in Docker and Docker Compose for creating consistent local development environments and production‑ready images. Static Analysis Configuration: Familiarity with enforcing code quality standards using ruff for linting and pyright for strict static type checking. #J-18808-Ljbffr