Lead AI Engineer (AI Systems & Automation)

Bjak•Madison, MS

5d•Remote

About The Position

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.

Requirements

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.
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.

Responsibilities

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.