Python Backend Engineer for Energy Data & AI Platform

Modo Energy; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Equity

Hybrid work schedule

Top-of-market compensation

Job summary

Modo Energy is hiring backend Python engineers to join our product teams, building production systems from day one with ownership over what you ship. You’ll work on the Modo Terminal, data pipelines, and an AI Analyst, leveraging AWS, Terraform, and modern Python frameworks.

We value fast learners who can move across the stack, own end‑to‑end features, and collaborate with energy analysts, data scientists, and modellers to deliver accurate data products and scalable pipelines.

Qualifications

• 3+ years of professional Python experience with backend focus.
• Hands-on experience with AWS and infrastructure-as-code (Terraform).
• Proficiency with Django, FastAPI, or similar async Python framework.
• Experience with data pipelines and PostgreSQL for scalable data services.
• Expert-level use of AI coding tools; know when to intervene and leverage them.
• Fast learner with good judgement and willingness to span the stack.

Responsibilities

• Build and maintain backend services and APIs powering the live product.
• Design and operate data pipelines that ingest, transform, and serve energy data at scale.
• Own AWS infrastructure end-to-end from development to production using Terraform.
• Create monitoring, observability, and alerting to pre-empt issues.
• Balance feature shipping with platform health and reliability.

Skills

Python

Django

FastAPI

AWS

Data pipelines

PostgreSQL

AI coding tools

System design

End-to-end ownership

Tools

Terraform

GitHub Copilot

Job description

Modo Energy is hiring backend Python engineers to join our product teams, building production systems from day one with ownership over what you ship. You’ll work on the Modo Terminal, data pipelines, and an AI Analyst, leveraging AWS, Terraform, and modern Python frameworks.

We value fast learners who can move across the stack, own end‑to‑end features, and collaborate with energy analysts, data scientists, and modellers to deliver accurate data products and scalable pipelines.