AI Backend Engineer (AI Workflow Systems)

Bjak•Madison, MS

2d•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 follow-ups. We are looking for talented AI Backend Engineers to build the systems that power AI-driven decisioning, automation, and orchestration across our platform. This role sits at the core of our AI stack - between models, backend systems, and real users - where latency, correctness, reliability, and cost directly impact production experience. This is a fully remote position where you will be part of a global engineering team working across multiple countries to build reliable, scalable AI systems.

Requirements

Strong backend engineering experience in production systems.
Experience building or operating high-throughput, low-latency services.
Familiarity with AI systems (LLMs, embeddings, or AI workflows).
Experience with distributed systems and production debugging.
Strong understanding of APIs, data flows, and system design principles.
Experience with observability tools (logging, monitoring, tracing).
Strong ownership mindset and bias toward shipping.
Comfortable working in fast-paced, globally distributed teams.
Thinks in systems, not just services or endpoints
Strong ownership of production behavior and system outcomes
Comfortable working with ambiguity and evolving requirements
Strong attention to failure modes, latency, and reliability
Focused on real-world production impact over theoretical design
Moves fast while maintaining engineering discipline
Obsessed with making systems stable, observable, and scalable

Nice To Haves

Engineers who only build features without owning production systems
Those uncomfortable debugging distributed systems under load
Developers who avoid responsibility for production incidents
Engineers who require perfect specifications before starting work
People who treat AI systems as black boxes without operational ownership

Responsibilities

Build and operate backend systems that serve AI-powered insurance workflows in production.
Design and implement AI orchestration layers that connect models, APIs, workflows, and business logic.
Build inference pipelines for LLM-based and AI-assisted automation systems.
Optimize latency, throughput, and cost across AI services (caching, batching, streaming, routing).
Design stable service boundaries between backend systems, ML components, and product APIs.
Implement observability: logging, metrics, tracing, alerting, and incident response workflows.
Debug production issues across distributed AI systems and resolve root causes.
Collaborate closely with frontend, product, operations, and ML teams to ship end-to-end features.
Continuously improve system reliability, scalability, and performance.