At a Glance
- Tasks: Build and maintain backend services and APIs for energy market professionals.
- Company: Join Modo Energy, a fast-growing data platform in the energy transition.
- Benefits: Top compensation, equity, hybrid work model, and career growth opportunities.
- Other info: Collaborative team environment with autonomy and ownership from day one.
- Why this job: Make a real impact in the energy sector with cutting-edge technology.
- Qualifications: 3+ years of Python experience and strong backend fundamentals required.
The predicted salary is between 56700 - 69300 £ per year.
About Modo Energy
The energy transition is the biggest infrastructure buildout in human history.
Modo Energy is the data platform at the centre of it.
We build the benchmarking, forecasting, and valuation tools that the world's most serious energy investors, developers, and operators depend on to make decisions.
If a battery gets financed, built, or traded anywhere in the world, there's a good chance Modo data was in the room.
Founded in 2019, we're 80+ people across London, New York, Sydney, and Madrid; $30M Series B, AI-native, and moving fast.
This is a rare chance to join a category-defining company at the moment it's scaling globally.
The Role
Modo Energy's engineering team builds the systems behind the Modo Terminal, the data, research, and agentic platform that energy market professionals rely on every day.
We're growing fast, and our ambitions are growing faster: from serving data and research to letting users (and their AI agents) query, forecast, and act on it directly.
We're hiring backend Python engineers to join one of our product teams: Terminal, Data, Ko (our AI Analyst), or Modelling.
Each team owns a business capability end-to-end, including its own APIs, data pipelines, AWS infrastructure, and developer tooling.
Wherever you land, you'll be building production systems from day one, with ownership over what you ship and how.
We're looking for engineers who learn fast and go wide.
You won't be boxed into a single layer of the stack; the best people on our teams move fluidly between building a feature, hardening a pipeline, fixing an infra issue, and automating away the next one.
If you're the kind of engineer who picks up a new tool, library, or part of the codebase without needing much of a runway, this is built for you.
What You'll Do
- Build and maintain backend services and APIs, on Django, Fast API, or similar, that power a live product used daily by energy market professionals.
- Design and operate data pipelines that ingest, transform, and serve energy market data reliably and at scale.
- Own AWS infrastructure and deployment end-to-end using Terraform, from local development through to production.
- Build the monitoring, observability, and alerting that let your team catch problems before customers do.
- Split your time between shipping new features and keeping the platform healthy.
Maintenance, performance, and production issues are a normal, expected part of the job, not an interruption to it.
- Design internal tools such as CLIs, APIs, and MCP servers that make your team and others faster, and that let both humans and AI agents work with our data safely and effectively.
- Work directly with the people who understand the domain (energy analysts, data scientists, modellers) to make sure what you build is accurate and actually useful.
- Contribute to the infrastructure behind our LLM-powered AI Analyst as needed: retrieval pipelines, tool-calling, and the plumbing that lets models work with real energy market data.
- Cross into the parts of the stack outside your core comfort zone when the team needs it, whether that's a bit of frontend or a bit of deeper infra, and pick up what you don't already know.
- What We’re Looking For The Essentials
- 3+ years of professional Python experience, with strong backend fundamentals.
- You write clean, well-structured code and are comfortable owning something end-to-end, from design through deployment and monitoring.
- Real, hands-on experience with AWS and infrastructure-as-code (Terraform). You've run production infrastructure, not just experimented with it.
- Proficiency with Django, Fast API, or a comparable async Python framework.
- Experience with data pipelines and relational databases (Postgre SQL), and building systems that serve data reliably at scale.
- Expert-level use of AI coding tools (Cursor, Claude Code, Git Hub Copilot, or similar). You know when to trust them, when to intervene, and how to get real leverage from them.
- We write a lot of code this way.
- A fast learner with good judgement, comfortable making calls on system design and what's good enough to ship, and genuinely energized by picking up unfamiliar tools, stacks, or problem areas rather than staying in one lane.
- Comfortable in a small, fast-moving team where you're expected to figure things out, make trade-offs, and ship, with real autonomy over how.
- Nice to have
- Experience with LLM-powered applications: RAG pipelines, tool-calling architectures, or agentic systems.
- Experience designing external-facing APIs, including versioning, backwards compatibility, and Open API/REST standards.
- Familiarity with data infrastructure such as Airflow, Spark, Iceberg, or Kafka.
- Experience with energy markets.
- Equal Opportunity
Modo Energy is an equal opportunity employer.
Employment decisions are made on the basis of qualifications, merit, and business need.
We do not discriminate on the basis of race, colour, religion, national origin, sex, age, disability, sexual orientation, gender identity or expression, pregnancy, or any other characteristic protected by law.
If you require assistance or a reasonable accommodation during the application or interview process, please contact us at careers@modoenergy. com.
What You Can Expect From Us
At Modo Energy, we believe that exceptional work deserves exceptional reward.
We're a high-performance team; ambitious, collaborative, and genuinely motivated by the scale of what we're trying to build.
You'll have real ownership from day one, work alongside some of the brightest people in the industry, and be part of a company that defining a new category in the global energy market.
We're hybrid: everyone works Tuesday to Thursday in office, with Monday and Friday flexible.
We offer top-of-market compensation, equity for every employee, and the space to take your career wherever you want it to go.
We're looking for people who want to do the best work of their careers.
If that's you, we want to talk.
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Python Engineer (Terminal/Modelling/Data) employer: Doist
Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.
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We think this is how you could land Python Engineer (Terminal/Modelling/Data)
✨Join Local Tech Meetups
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Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
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How to prepare for a job interview at Doist
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Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.