Systems AI Engineer

Why this role exists

Most systems work at a low scale.

Very few survive real production load, complex workflows, and enterprise edge cases.

We are building a platform that must

Scale from 500K → 20M+ interactions/month

Handle complex insurance workflows reliably

Become easier to deploy as it grows, not harder

This role exists to build the backend foundation that makes this possible.

What you’ll do

You will not just write services.

You will design and own core platform systems.

Scale the platform without breaking architecture

Scale from 50K → 4M+ interactions/month

Ensure

High availability

Low latency

Fault tolerance

Avoid large rewrites — build systems that evolve cleanly

Build the workflow automation (WA) engine

Design a flexible system with

States

Stages

Cohorts

Dynamic workflows

Ensure workflows

Handle edge cases reliably

Can be configured easily

Move from

Hardcoded flows → configurable execution engine

Build the insurance-specific data layer

Design data models for

Policy states

Claim workflows

Consent tracking

Ensure the system works across

Multiple insurers

Multiple use cases

Build a platform-first data layer, not use-case-specific hacks

Make deployment and setup simple

Ensure workflows and data models are

Easy to configure

Easy to launch

Reduce friction for

Product teams

Deployment teams

Create a compounding data advantage

Build a data layer that

Improves with every deployment

Captures structured signals

Ensure data becomes a long-term edge, not just storage

Own production reliability

Participate in on-call rotation across 3 engineers

Ensure

Incidents are handled quickly

Root causes are fixed permanently

Build systems where reliability is shared, not individual

What success looks like

Platform scales to 2M+ interactions/month smoothly

Workflow engine supports complex, dynamic use cases

Data layer enables fast deployment across accounts

Edge cases are handled without constant firefighting

System becomes easier to use as it grows

Production issues are rare and predictable

Who you are

You have built

Scalable systems

Distributed services

You think in

Systems

Data models

Trade-offs

You are comfortable owning

Architecture

Production systems

What will make you stand out

Experience building

Workflow engines

State machines

Data-heavy platforms

Strong understanding of

System design

Distributed systems

Failure handling

Experience working in

High-scale production environments

Why join

You will build the core backend of an AI platform

Your work directly impacts

Scale

Reliability

Product capability

You will design systems that move from

Use-case specific → platform-level infrastructure

What this role is not

Not just API development

Not limited to feature-level work

Not disconnected from production realities

What this role is

A system architect

A builder of scalable platforms

A driver of long-term technical advantage

One question to self-evaluate

Can you design backend systems that scale, handle edge cases, and become easier to use as they grow?