Capsa AI
Engineering Manager

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The AI Operating System for Private Capital
Capsa AI
Private capital funds have to find potential investments, research and analyse them thoroughly, monitor them over time, drive improvements, and decide when to buy and sell. They've got to see through the marketing. They've got to outbid the competition. And they've got to learn from every deal they do. Historically, these processes have run on people, we are building the AI Operating System that will run them in the future.
We're focused, ambitious, and obsessed with building a category-defining company. In the last 12 months we've grown ARR 15x, achieved product–market fit with leading multi-billion-dollar PE firms, and expanded across the US, UK, and Europe. Now we're doubling down: we've raised a large Series A from top-tier VC investors to scale the team. We're hiring hyper-talented people who want to work at the forefront of AI and revolutionise an industry.
The role
You’ll manage the engineers across three squads (intelligence, experience and platform), own hiring and people development, and strengthen technical leadership within each team.
You’ll partner with the product managers in Intelligence and Experience and the squads’ technical leads to translate company priorities into clear objectives, shape solutions together, and agree credible delivery plans. You’ll make sure engineers contribute to understanding customer problems and exploring solutions rather than just implementing requirements.
Across the three squads, you’ll be accountable for engineering capability, the quality of our work, and delivery against agreed commitments. You’ll make capacity, dependencies and risks visible, resolve obstacles, and work with Product and the CTO when priorities, scope or timing need to change. Alongside the squads and Product, you’ll share responsibility for the outcomes the work achieves.
The opportunity
You’ll own hiring, coaching and performance management across all three squads, developing engineers and technical leads who can make good decisions and take responsibility for their work.
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.
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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.
There’s real scope to shape engineering management at Capsa, working with the CTO and Product to establish clear responsibilities and a consistent operating approach in a lean, flat structure.
You'll work alongside a small, senior and high performing engineering team
- Meaningful equity in a company that grew ARR 15x last year
What you'll achieve in the first six months
- Formed an evidence-based view of the codebase, delivery process and engineering capability across all three squads, and agreed the most important improvements with the CTO and Product.
- Made your first hiring and team-shape decisions, grounded in the capabilities and capacity each squad needs.
- Established regular coaching and clear expectations for your engineers, with a grounded view of who’s thriving, who needs support and where the gaps are.
- Established clear technical ownership within each squad, with engineers taking responsibility for decisions and technical leads working effectively with Product.
- Helped the squads deliver meaningful improvements end to end, and assessed their impact on customers or the teams that depend on them.
- Put an agreed, lightweight planning and delivery rhythm into practice across the squads, making commitments, dependencies and risks visible without centralising every decision.
Recent projects from the team
- Agent Harness: our own agent harness built on a custom, streaming-first graph execution framework
- Code Execution Framework: interruptible and resumable mid-execution, for programmatic tool calling
- Document Ingestion, Indexing, and Search: a VLM-based OCR pipeline, a self-hosted search cluster, domain-aware search strategies
- Citations: an end-to-end approach to reviewing supporting documentation behind AI-generated statements
- Document Authoring: agent tooling and a document editor supporting collaborative authoring across Word, Excel, PowerPoint, and email


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Track record
- Managed engineers directly for a few years; before that, a strong individual contributor at a venture-backed startup or a serious tech company
- You’ve coordinated work across teams or substantial parallel workstreams, resolving dependencies and competing demands while keeping ownership with the engineers doing the work.
- Hired people, developed them, and made calls about team shape as things scaled or didn't go to plan
- Shipped distributed systems, data pipelines, or platform services to production through a team you led
- Comfortable operating at pace, with incomplete information
How you operate
- Takes responsibility for what your team ships and its effect on customers, not just internal velocity metrics
- Thinks carefully about the problems being solved and the decisions the team makes; uses AI to sharpen that thinking, not replace it
- Accepts that time is short and information is incomplete, makes progress anyway, and adjusts as more is known
If this opportunity excites you
We'd like to meet you. Initial conversations are direct and substantive, going deep on the work, the team, and what you'd own in the first six months.
Capsa AI provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.
Capsa AI is committed to a fair and transparent hiring process. We confirm that this advertisement is for an active, existing vacancy within our organization. Please be advised that we may use artificial intelligence-driven tools to assist our recruitment team in screening, assessing, and selecting candidates for this position.
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