Software Enginee , Data & AI Platform

Axiamatic; Menlo Park (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Axiamatic in Menlo Park, CA, is seeking an experienced backend engineer to shape the architecture and engineering practices for our agent-orchestration layer on frontier LLMs. You will turn heterogeneous program data into structured, queryable knowledge that agents can reason over and build reliable services across workloads.

You will own backend features end to end, collaborate with product management and customers, review code, write tests, and drive production quality in a fast-moving startup

Qualifications

• BS, MS, or PhD in Computer Science or a related field.
• 2–4 years building backend systems in production, ideally 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.
• Experience with cloud services, AWS preferred.
• Comfortable in a fast-moving startup environment.

Responsibilities

• Shape architecture and engineering practices for the agent-orchestration layer on frontier LLMs.
• Turn heterogeneous program data into structured knowledge that agents can reason over.
• Build reliable, observable, and cost-efficient backend services across workloads.
• Own backend features end to end from design through deployment and operation.
• Collaborate with product management and customers to decide what to build.
• Review code and write tests for production quality.

Skills

Python

API design

Backend development

Cloud infrastructure

LLM integration

Education

BS/MS/PhD in Computer Science or related field

Tools

Java

AWS

Docker

Job description

Menlo Park, United States | Posted on 09/01/2026

Axiamatic builds an agentic platform that de-risks enterprise transformation programs: the multi-year ERP, CRM, and supply-chain overhauls that routinely slip on cost and timeline. Our agents ingest a program’s real signals, catch risk before it compounds, and route remediation to the right people. Fortune 500 programs already run on it. (More at axiamatic.com.)

We’re a Series A startup backed by multiple top-tier Silicon Valley VCs, with founders who have built and exited companies together. Two problems sit at the center of the work: turning messy, real-world program data into structured knowledge, and building the agent layer on frontier LLMs that acts on it.

What you’ll do

• Help shape the architecture and engineering practices for our agent-orchestration layer on top of frontier LLMs.
• Turn heterogeneous program data (plans, status reports, risk registers, meeting notes) into structured, queryable knowledge that agents can reason over.
• Build services that stay reliable, performant, observable, and cost-efficient across conventional and LLM-driven workloads.
• Own backend features end to end, from problem definition and technical design through deployment and production operation.
• Work directly with product management, and with the messy realities of how customers actually operate, to decide what’s worth building, not just how to build it.
• Review code, write tests, and share responsibility for what’s running in production.

Requirements

• BS, MS, or PhD in Computer Science or a related field.
• 2-4 years building backend systems in production, ideally for AI-powered or data-intensive products.
• Strong Python and solid backend fundamentals: API design, concurrency, distributed services, testing, and production debugging. Some of our services are in Java, so you’re comfortable there or ready to pick it up.
• Experience shipping an LLM-powered feature to production, with real ownership of how it behaves, not just a prototype. Familiarity with model APIs, retrieval, and agent workflows.
• A feel for structuring messy, real-world data: you’ve taken unstructured or heterogeneous sources and turned them into something a system can rely on.
• Hands-on experience building on a public cloud, AWS preferred.
• Comfortable in a fast-moving environment where priorities evolve with the product; you’re the kind of engineer who takes an open-ended problem, shapes the approach, and drives it to something shipped.
• Startup experience is a plus.

Work model: Hybrid, 3 days a week in our Menlo Park office