Senior Software Engineer, Python

We’rehiring a Senior Software Engineer to join ourEconomicsTeam.You’llhelp design,buildandmaintainthecalculationlogic,dataflowsand infrastructurethat powerComboCurve’sEconomics engine. This role is ideal for someone who loves writing modern Python, caring about architecture and testability, and buildingnew featuresthat makeComboCurve’splatformevenmore powerful.

WhatYou’llDo 

• Write efficient Python code on structured time series datasets thatscaleseasily across cloud infrastructure.

• Own features end-to-end—from scoping and design through implementation, deployment, and monitoring—working as an independent unit alongside our Product Manager.

• Engage in software and infrastructure system design discussions, contributing to architectural decisions that shape theComboCurveplatform.

• Build andmaintainbackend services and APIs in Python that are reliable, well-tested, and straightforward to extend.

• Model, query, andoptimizedata in MongoDB—schema design, indexing, and aggregation pipelines—so product features stay fast as data grows.

• Deploy andoperatecontainerized services on cloud infrastructure, leveraging GCP components such as Cloud Run, Cloud Functions, and GCS.

• Incorporate AI-first development practices—using AI tooling to accelerate delivery, improve code quality, and explore new product capabilities.

• Collaborate with engineering peers through code reviews, technical documentation, and shared standards that raisecodequalitythe team.

Requirements

Technical

• Python:Production-grade Python 3.13+, type annotations and async/await as the default. No shortcuts on type safety.

• API Design:Clean REST orgRPCservices withOpenAPIcontracts.Knowshow to version and evolve APIs without breaking consumers.

• Web Frameworks & Serving:Hands-on experience with Flask and/orFastAPIfor building production services, and comfortable configuringGunicornfor WSGI deployment.

• Software Architecture Patterns:SOLID principles and clean architecture in practice. Designs decoupled, maintainable services that scale.

• Data & Statistical Analysis:Comfortable working with structured datasets in Python using tools like pandas ornumpyfor basic statistical analysis, exploratory analysis, and deriving actionable insights from data.

• Data Processing & Visualization:Able to process medium-to-large datasets efficiently and communicate findings clearly through simple visualizations or reports when needed.

• SaaS Delivery:Proventrack recordtaking features to production in cloud-based SaaS products. Comfortable with the full lifecycle from dev to deploy tomonitor.

• MongoDB:Schema design, indexing, and aggregation pipelines in production. ODM likeMongoEngineor native driver,e.g.PyMongo.

• Modern Dependency Management:Hands-on withuvor similar for fast package resolution and virtual environment handling.

• Testing:Comprehensivepytestsuites including fixtures, parameterization,and mockedexternal services.

• Containerization:Docker and Docker Compose forlocal andproduction.Knowshow to keep images lean.

• Code Quality:Enforces standards via tools like ruff andpyright. Treats static analysis as a first-class concern.

Nice to Have

• Google Cloud Platform:Deploying and managing services on GCP, specifically Cloud Run, Cloud Functions, andCloudStorage.

• AI Integration:Exposure to LLM APIs or agent frameworks; ability to wire AI capabilities into product features without needing to be an ML specialist.

• DomainKnowledge:Experiencein the oil and gas industryor abackgroundinPetroleum Engineering;the context matters here and shapes better product decisions.

Workflow & Collaboration

• Takesownership end-to-end, from scoping to shipping to iterating.

• Can translate ambiguous product requirements into concrete technical proposals.

• Communicates tradeoffs clearly to both engineers and non-technical stakeholders.

• Reviews code to raise quality and share context, not just approve.

While this is a fully remote position, there will be an inpersonNew Hire Orientation.