Lead AI Engineer (AI Systems & Automation) at Bjak

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

26 Sep, 26

Salary

0.0

Posted On

28 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI System Design, LLM Orchestration, Backend Engineering, Distributed Systems, Python, Node.js, Kubernetes, Docker, SQL, NoSQL, Observability, Inference Pipelines, System Architecture, Technical Leadership, API Integration, Root Cause Analysis

Industry

Software Development

Description

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. 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. 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.

Responsibilities

Lead the design and delivery of production-grade AI systems and orchestration layers to automate insurance workflows. Drive engineering standards for reliability, scalability, and observability while mentoring other engineers.