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Software Engineer
About the Role
You've found your footing. You can build features end-to-end with timely guidance, you're starting to see how the bigger systems fit together, and you're getting a feel for which technical choices will hold up. That's the moment we want you in. You'll join a squad doing real engineering on a platform that legal teams across the world rely on, and the AI shift in software is something you'll be living and shaping, not just reading about.
You can grow toward Senior and beyond. Internal progression is the default at Opus 2, and we hire externally only when there's no internal alternative.
What you'll do
- Deliver well-scoped features end-to-end. Small to mid-size pieces of work with timely guidance. You break down tasks, ship in slices, and see them land for users.
- Partner with Product and Design. Translate intent into pragmatic, well-scoped technical work. Ask the questions that surface tradeoffs early.
- Pull others up while you grow. Help juniors. Review their code well. The mentoring habit starts here, not at senior.
- Use AI tools well across the SDLC. Daily workflow, exploration, knowledge-sharing. Bring back what you find to the team.
- Improve the system. Documentation that was missing, a flaky test, observability you wish you'd had. You leave things better than you found them.
The shape we're hiring for
We're growing engineers toward a T-shape: broad across the stack, with depth starting to form in at least one area. At this level, breadth comes first; depth begins to emerge.
- Generalist breadth across the team's stack. You're not blocked by "that's not my layer" when a feature spans frontend, API, data, and deployment.
- Depth starting to form. You're developing a stronger area, the one your colleagues come to you for. By the upper end of this band, that's noticeable.
- Ownership of the work you commit to. Outcomes, not just output. You finish what you start, and ambiguity is something you push through rather than something that stalls you.
- Pragmatism. You favour simple, testable solutions and ask for help when complexity gets ahead of you.
- Coaching the level below. You answer questions clearly. You give code review feedback that grows people rather than feedback that's just correct.
- Change disposition. You treat change in tools and ways of working as part of the job. You learn fast and bring it back to the team.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
You'll be a strong fit if
- You've shipped real production code and can tell the story of how it was used and how it failed.
- You're comfortable across the team's stack (backend, frontend, data, deployment) even if you have a stronger area.
- You're using AI tooling in your daily workflow and curious about where it fits in the product.
- You enjoy improving the work around you (code, docs, processes), not just adding to it.
- You've grown through code review and feedback, and you give it back generously.
You might be a less good fit if
- You want fully specified tickets and nothing else.
- You're not interested in helping more junior engineers grow.
- You'd rather specialise narrowly and not stretch outside your comfort zone yet.
- You'd rather hold off on AI tooling until others have proven what works. At this level, adopting and shaping it is part of the day job.
- You find rapid change in tools and ways of working draining rather than energising.
How we work
Opus 2 builds the platform that leading legal teams use to run their most complex work: a distributed, multi-tenant SaaS platform with API-first surfaces, where security, privacy, and compliance are first-class concerns. The stakes for our customers are real, so we care about quality. We also move fast and ship, because the alternative is irrelevance.
- Strong ownership. Squads own their products end-to-end, from the customer outcome through to operating them in production.
- Pragmatic engineering. We favour simple, testable solutions over premature abstraction. We use data where it informs a real decision.
- A learning and improvement culture. We're building an engineering organisation that learns and adapts at the pace AI is forcing on the work. That's the bar for hiring, growth, and how we run the team.
- Coaching as part of seniority. Senior engineers help juniors, mid-levels, and each other grow. We protect that time on calendars.
A work in progress
Opus 2 is in real transition. AI is reshaping how our customers work and how we build software, and we're investing in the engineering organisation to keep pace. Some of that is already settled; other parts are still being shaped.


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If you want a fully paved path, this isn't it yet. If you want to be an agent of change in a team that's clear about where it's going and pragmatic about how to get there, there's real leverage here. We're hiring people who'll help us shape this, not just slot into it.
Tech you'll work with
We pick tools to fit the problem, and we have a clear sense of where we're heading. On the backend we're investing in Python, Go, and TypeScript. Java and PHP are in established parts of the platform and we'll keep them well-tended where it makes sense. If you light up about Python or Go, you're in the right place.
- Backend: Python, Go, TypeScript (where we're investing); Java and PHP (established services)
- Frontend: React
- Deployment: Kubernetes primary; serverless where it's the better fit
- Cloud: AWS
- Data: Postgres, MongoDB, OpenSearch / Elasticsearch, vector stores
- AI: GenAI features already in production (LLMs, retrieval, agentic workflows), with more on the way
You don't need to know all of these on day one. You should be ready to learn what you don't.
Working for Opus 2
- Engineering work at a company where AI is real, in production, and a core part of how customers get value. Not a side-of-desk experiment.
- A focused engineering organisation where your work is visible, your decisions matter, and the path from idea to customer is short.
- Investment in your growth: coaching, learning time, exposure to challenging problems, and a clear path to Senior when you're ready.
- Contributory pension plan.
- 33 days annual holidays, flexible working, and length of service entitlement.
- Health Insurance.
- Loyalty Share Scheme.
- Enhanced Maternity and Paternity.
- Employee Assistance Programme.
- Electric Vehicle Salary Sacrifice.
- Cycle to Work Scheme.
- Calm and Mindfulness sessions.
- A day of leave to volunteer for charity or dependent day.
- Regular Company Social Events.
- Yearly Development Retreat.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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