Backend Engineer – AI Platform & LLM Orchestration

Axiamatic; Menlo Park (CA); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Axiamatic in Menlo Park, CA, is seeking a backend engineer to shape the agent-orchestration layer atop frontier LLMs. You will turn diverse program data into structured knowledge and build reliable, scalable services for AI-powered workloads.

We value ownership of production features, collaboration with product teams, and the ability to operate in a fast-moving startup environment with a hybrid work model.

Qualifications

• BS/MS/PhD in Computer Science or related field.
• 2–4 years building backend systems in production, preferably AI-powered or data-intensive.
• Strong Python and backend fundamentals: API design, concurrency, distributed services, testing, and production debugging.
• Experience shipping an LLM-powered feature to production with ownership of behavior.
• Familiarity with model APIs, retrieval, and agent workflows.
• Experience building on public cloud, AWS preferred.
• Ability to turn messy, real-world data into structured knowledge.
• Comfort with a fast-moving startup environment.

Responsibilities

• Help shape the architecture and engineering practices for our agent-orchestration layer on top of frontier LLMs.
• Turn heterogeneous program data into structured, queryable knowledge that agents can reason over.
• Build services that are reliable, performant, observable, and cost-efficient across workloads.
• Own backend features end to end from design to deployment and production operation.
• Collaborate with product management and customers to decide what’s worth building and how to build it.
• Review code, write tests, and share responsibility for production systems.

Skills

Python

API design

Concurrency

Distributed services

Testing

Production debugging

Java

LLM-powered feature

Model APIs

Retrieval

Agent workflows

AWS

Education

BS in Computer Science

MS/PhD in CS

Tools

Python

Java

AWS

Job description

Axiamatic in Menlo Park, CA, is seeking a backend engineer to shape the agent-orchestration layer atop frontier LLMs. You will turn diverse program data into structured knowledge and build reliable, scalable services for AI-powered workloads.

We value ownership of production features, collaboration with product teams, and the ability to operate in a fast-moving startup environment with a hybrid work model.