Bjak
Lead AI Engineer (AI Systems & Automation) - Remote (UK)

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BJAK
BJAK is Southeast Asia's largest digital insurance platform, building AI-powered products that simplify insurance and financial services for millions of users. We use AI and automation to transform real-world insurance workflows such as quotations, policy issuance, endorsements, claims, and customer operations.
We are looking for a Lead AI Engineer to own the design, development, and delivery of production AI systems across our backend and workflow automation stack. This role sits at the core of our AI platform - where model capabilities are translated into reliable, scalable, and production-grade systems that directly impact real users and business outcomes.
This is a fully remote role where you will be part of a global engineering team working across multiple countries to build reliable, scalable AI systems.
Focus
- Lead the design and development of production AI systems powering insurance workflow automation.
- Architect AI orchestration layers connecting LLMs, backend services, and business workflows.
- Own end-to-end AI system design, including inference pipelines, routing, caching, and fallback strategies.
- Drive engineering decisions around latency, reliability, cost, and scalability of AI services.
- Lead implementation of observability systems (logging, monitoring, tracing, alerting).
- Review and guide backend AI implementation across engineering teams.
- Collaborate with product, backend, DevOps, and operations teams to ship end-to-end AI features.
- Debug complex production issues across distributed AI systems and lead root-cause analysis.
- Define engineering standards and best practices for AI system development.
- Mentor engineers and elevate technical execution quality across teams.
Ideal Experience
- Strong backend or AI engineering experience in production environments.
- Experience building or scaling AI systems (LLMs, embeddings, recommendation systems, or automation workflows).
- Strong system design skills with experience in distributed systems.
- Experience with production inference pipelines and AI orchestration.
- Strong debugging ability in high-scale, latency-sensitive environments.
- Experience with observability, monitoring, and incident response.
- Proven ability to lead technical execution in cross-functional teams.
- Strong ownership mindset and ability to drive projects end-to-end.
- Comfortable working in fast-paced, globally distributed teams.
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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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.
Outcomes
- AI systems operate reliably at scale with strong performance and low latency.
- AI workflows are stable, observable, and production-grade across multiple products.
- System architecture supports rapid iteration without compromising reliability.
- Production incidents are quickly identified, resolved, and prevented.
- Engineering teams execute faster and with higher technical quality under your leadership.
- AI capabilities are deeply integrated into global insurance workflows.
Tech Stack
- Python
- Node.js
- LLM APIs (OpenAI / Anthropic / open-source models)
- SQL / NoSQL databases
- Kubernetes
- Docker
- Distributed systems tools
- Observability stack (logging, metrics, tracing)
How We Work
We believe strong products are built by small, high-ownership teams. Engineers at BJAK work closely with product, design, AI, and operations teams to solve meaningful, real-world insurance problems. We value technical excellence, speed of execution, and practical decision-making.
As a lead, you are expected to raise engineering standards, guide system design decisions, and ensure teams deliver reliable production systems.
Why Join BJAK
- Build AI-Powered Products - Work on intelligent insurance automation systems.
- Global Engineering Organization - Collaborate across multiple countries.
- International Impact - Products used by millions across Southeast Asia and beyond.
- Learning & Development Budget - Support continuous technical growth.
- High Ownership Culture - Lead critical AI systems end-to-end.
- Modern Engineering Practices - Strong focus on scalability and reliability.
- Leadership Impact - Shape AI architecture and engineering standards.
- Competitive Compensation - Attractive salary package.
- Fully Remote - Work remotely with globally distributed teams.


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The Kind of Builder We Want
- Strong systems thinker who connects AI, backend, and business workflows
- Hands-on technical leader who still writes and reviews production code
- Strong ownership of production systems and outcomes
- Calm under pressure with clear technical judgment
- Strong focus on reliability, scalability, and maintainability
- Ability to guide engineers without micromanaging
- Bias toward execution and real-world impact over theory
This Role Is Not For
- Leaders who only delegate without technical involvement
- Engineers who avoid production responsibility or incidents
- Those who cannot operate in ambiguous or fast-changing environments
- People who focus on architecture without accountability for execution
- Engineers who lack hands-on experience with production systems
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 in our hiring process and aim to make decisions promptly. 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 lead the development of AI systems powering real-world insurance workflows across global markets.
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Jessica, London
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