S&P Global Energy - Python Software Engineer The role: Python Software Engineer. Our Data Science and Modelling team drives innovation by transforming complex commodity data into actionable insights that impact integral business decisions.
We're a collaborative, goal-oriented group working in a dynamic environment where you'll leverage cutting‑edge AI and automation technologies alongside talented data scientists, engineers, and domain experts who value continuous learning and creative problem‑solving.
Responsibilities:
- Build and maintain retrieval‑augmented generation (RAG) applications and LLM‑powered solutions using vector databases and orchestration frameworks to enhance data retrieval and generation capabilities.
- Work with business teams to analyze data, build pipelines, and identify automation opportunities.
- Drive business decisions based on insights obtained from data.
Qualifications:
- Bachelor's degree in Computer Science, Engineering, or related discipline.
- Strong experience in object‑oriented programming with the ability to design and develop modular, maintainable code, and a solid understanding of design patterns and SOLID principles, including advanced use of distributed version control systems for collaborative development.
- 5+ years of programming experience with 3+ years of Python; and a strong understanding of data pipelines, machine learning implementation, and clean code practices.
- 1+ years hands‑on experience building and deploying LLM‑based applications, including RAG architectures using orchestration frameworks, vector databases, and LLM operations/monitoring tools.
- 2+ years of experience accessing and manipulating data with relational or NoSQL databases.
- Excellent written and spoken English communication skills with the ability to translate technical concepts for non‑technical stakeholders.
- Collaborative team player who thrives in Agile environments.
- Knowledge of cloud services, big data technologies, large‑scale data analytics tools, and API integration.
Location: Mexico or Colombia remote.
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