Python Developer

About ROGII & The Project

ROGII develops cutting-edge geoscience and geosteering platforms for the oil & gas industry, enabling real-time well steering, well log visualization, subsurface mapping, and trajectory planning. Our platform covers the full workflow from well planning through completion and is trusted by operators and service companies worldwide.
As part of the ROGII ecosystem, we are building specialized services for automated data processing. These tools serve as a force multiplier for our users—enabling faster decision-making and drastically reducing manual data entry for field engineers.
In this role, you won't just be writing code in a vacuum; you will work closely side-by-side with our drilling engineers and domain experts. This collaboration ensures our LLM pipelines accurately interpret the technical nuances of the oilfield, turning complex engineering data into structured, actionable insights.

Responsibilities

• Domain Collaboration: Partner with drilling engineers to understand the specific logic of drilling operations, ensuring the service meets real-world field requirements.
• API & Backend: Maintain and extend the REST API built on FastAPI and Pydantic.
• LLM Pipeline Development: Build and optimize extraction pipelines that identify business-critical data from unstructured reports.
• Quality Assurance: Write integration tests and analyze extraction accuracy via Langfuse.
  
  

Tech Stack

• Core: Python 3.11+, FastAPI,  Pydantic, asyncio, pytest
• AI/LLM: OpenAI SDK, Langfuse
• Infrastructure: Docker, Kubernetes, MinIO/S3, Redis (task queues), GitLab CI/CD
  
  

Requirements

• 1–3 years of commercial Python development experience.
• Strong Mathematical Foundation: Linear algebra, statistics, and numerical methods.
• Pure Python Computation: Ability to implement clean, complex calculations using standard data structures without relying on external libraries like pandas or numpy when necessary (you must understand what happens "under the hood").
• Data Ecosystem: Solid knowledge of pandas, numpy, and scipy for analysis and prototyping (knowing when to use them vs. when to write from scratch).
• Async Proficiency: Experience with FastAPI or similar async frameworks and a deep understanding of asyncio.
• Reliability: Experience writing automated tests (pytest) and a basic understanding of Docker.
• English: B2+
  
• Availability to work on- site in Puerto Madero, Ciudad Autónoma de Buenos Aires 
  

Nice-to-Have:

• Experience integrating with OpenAI API or other LLM providers.
• Working with task queues (Celery, arq, or RQ).
• Experience with S3-compatible storage and user-level Kubernetes.
• Familiarity with observability tools (Prometheus, Jaeger, OTLP).
• Experience parsing complex PDFs (coordinate systems, tables).