Bjak
Technical Lead, AI Email App

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About the Role
There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting.
Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. We believe products will greatly reduce hallucinations.
Our objective is to organise anyone's life, allowing us all to spend time on valuable and meaningful things.
Role Overview
As Technical Lead, AI Email App, you own the engineering layer that turns AI capability into a reliable product. You will shape the architecture across backend services, APIs, and client applications, while leading a small team of senior engineers.
This is a hands-on leadership role. You stay close to the code, make critical architectural decisions, and ensure the system remains fast, reliable, and coherent as it scales.
What You'll Own
- Own the application engineering strategy and execution across backend, mobile, and desktop.
- Design reliable systems for AI-powered workflows, including state, orchestration, tool use, retries, fallbacks, and failure handling.
- Build the APIs and abstractions that connect AI systems to real-world product experiences.
- Lead a small, senior engineering team and raise the technical bar through design reviews, code reviews, and hands-on mentorship.
- Make high-impact trade-offs across latency, reliability, cost, security, and user experience.
- Establish strong production foundations: observability, monitoring, testing, and operational excellence.
- Partner closely with ML leadership to turn model capabilities into robust, shippable product experiences.
- Move quickly while keeping the architecture simple, maintainable, and ready to scale.
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.
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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.
What We're Looking For
- Significant experience leading application or product engineering for complex systems.
- Strong hands-on background building and shipping backend systems used in production.
- Experience building AI-powered products or systems that integrate with modern ML/LLM capabilities.
- Strong technical judgment and the ability to make decisions with incomplete information.
- Comfortable working across backend and client platforms, with deep expertise in at least one.
- A strong bias toward ownership, shipping, and learning from real-world usage.
- High standards for code quality, reliability, and engineering fundamentals.


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Outcomes
- Production systems are observable, monitored, and stable under real-world load.
- Decisions consistently balance speed, cost, reliability, and user experience.
- Features across backend, mobile, and desktop work smoothly and reliably.
- Latency and reliability improve measurably over time.
How We Work
We are a small, high-talent-density, hands-on team. Engineers have broad ownership and are expected to exercise strong judgment and execute independently.
We make decisions quickly, work closely together, and balance speed with engineering fundamentals. We care less about process and more about building something exceptional.
Interview Process
If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.
Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.
We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.
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