Role Purpose
NOA is looking for 4 exceptional full‑stack software engineers (with 10+ years of experience).
You'll work within a cross‑functional, empowered product team alongside product management and design, solving hard problems in the energy trading and renewable energy domain. Our teams follow the product operating model – engineers participate in product discovery, assess feasibility, prototype solutions, and deliver outcomes. You won’t be shielded from the business; you’ll have direct exposure to customers, end users, domain experts, and the complex real‑world problems our software needs to solve.
What you will do
- Solve real problems, not just ship features. Work with your product team to understand customer pain, evaluate technical approaches, and deliver solutions that move the business forward.
- Build across the full stack. Design and implement backend services in Python/Django, build front‑end interfaces in JavaScript/TypeScript, and work with cloud infrastructure on AWS.
- Translate complex domain logic into well‑architected software. Work closely with energy and financial domain experts – turning complex business models and spreadsheet‑based workflows into robust, scalable systems.
- Drive engineering quality. Write clean, tested, maintainable code. Contribute to architectural decisions, code reviews, and engineering standards as we build the foundation of our platform.
- Leverage AI tools to maximise your impact. We expect engineers to actively use AI coding tools (we primarily use Claude, but experiment broadly) to accelerate their work without compromising quality.
- Shape the engineering culture. We're in the early stages of building a world‑class product and engineering organisation. You'll help establish practices, processes, and norms – not just inherit them.
- Serve as the technical voice on your product team – partnering with product managers and designers to assess feasibility risk and drive technical discovery.
- Mentor and elevate junior engineers through pairing, code review, and architectural guidance.
- Make strategic technical decisions that balance short‑term delivery with long‑term platform health and scalability.
- Take ownership of cross‑cutting concerns: system architecture, reliability, performance, and security.
What we’re looking for
Must have skills & experience
- Strong Python backend skills – significant experience building production systems with Python and Django (or Django REST Framework).
- Full‑stack capability – comfortable working across backend, front‑end (JavaScript/TypeScript), databases, and infrastructure. You don’t need to be an expert in all layers, but you must be willing and able to work across them.
- Cloud platform experience – hands‑on experience with AWS (preferred) or another major cloud provider.
- Relational database proficiency – solid experience with PostgreSQL or similar.
- Product‑minded engineering – you think about the "why" behind what you build, not just the "how." You’re comfortable participating in product discovery alongside product managers and designers.
- Strong problem‑solving instincts – you break down complex, ambiguous problems into clear technical approaches.
- Effective communication – you can articulate technical decisions clearly to both technical and non‑technical colleagues.
- AI‑augmented workflow – you actively leverage AI coding and productivity tools to accelerate your work and improve quality, and understand how to use AI safely and responsibly.
- Relevant qualifications and experience – ideally a degree in Computer Science, Computer Engineering, Electronic Engineering, or a related field, combined with relevant professional experience of 10 to 20 years. Qualifications and years of experience are a guide, not a gate. If your skills and impact exceed what your CV timeline suggests, we want to hear from you.
Great to have skills & experience
- AWS architecture and security – including networking, IAM, and infrastructure‑as‑code (Terraform).
- DevOps and platform engineering – CI/CD pipelines, containerisation (Docker), monitoring, and reliability.
- Data engineering – data lakes, ETL/ELT pipelines, large‑scale data processing, analytics architecture.
- Front‑end architecture – experience leading front‑end technology choices and building modern JavaScript/TypeScript applications.
- Energy sector or energy trading experience – familiarity with complex, technical domain‑heavy environments.
This role is a great fit if…
- Are motivated by impact and learning – you want to build something meaningful, not just collect a title.
- Thrive in ambiguity and rapid change – you’re energised, not paralysed, when requirements are still forming.
- Are flexible across technical functions – you’ll happily pick up work outside your core capabilities when the team needs it.
- Are eager to learn a complex new domain – our energy trading business is intellectually demanding and you’ll need to get up to speed quickly.
- Have a builder’s mindset – you’d rather roll up your sleeves and ship something imperfect than wait for a perfect specification.
- Want to shape a culture, not just fit into one – we’re actively building our engineering practices and product operating model, and you’ll have a direct hand in defining how we work.
This role might not be for you if…
- You prefer working within a narrow technical field and aren’t interested in working across the stack.
- You're not open to working in Python and Django.
- You're not motivated to learn new tools, frameworks, and AI‑assisted workflows.
- You prefer well‑established processes and a stable, predictable environment – we’re a startup and things move fast.
- You want to be told exactly what to build – our engineers are expected to help figure out what to build, not just how.
Tech Stack
- Backend: Python, Django, Django REST Framework
- Front‑end: Mostly JavaScript on Django UI for now while our long‑term front‑end strategy is being developed.
- Database: PostgreSQL
- Infrastructure: AWS, Terraform, Docker
- CI/CD: GitHub Actions
- Orchestration: Apache Airflow, MWAA, Ploomber
- AI tools: Claude (primary), GitHub Copilot, plus continuous experimentation across the AI ecosystem
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