Software Engineer , Data & AI Platform

Axiamatic; Menlo Park (CA); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Axiamatic seeks a backend engineer to shape the architecture for an agent-orchestration layer on frontier LLMs. You will turn diverse program data into structured knowledge and build reliable services that scale in production.

You will own backend features end to end and collaborate closely with product teams and customers to decide what to build. The role requires 2–4 years in production backend work, strong Python skills, and experience with cloud (AWS).

Qualifications

• BS, MS or PhD in Computer Science or related field.
• 2-4 years building backend systems in production, AI/powered or data-intensive products.
• Strong Python and backend fundamentals; some Java experience is fine.
• Experience shipping an LLM-powered feature to production with ownership.
• Familiarity with model APIs, retrieval, and agent workflows.
• Experience structuring messy data for reliable systems.
• Hands-on with public cloud, AWS preferred.
• Startup experience is a plus.

Responsibilities

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

Skills

Python

Backend design

APIs

Distributed systems

Testing

Cloud

Education

BS/MS/PhD in CS

Tools

AWS

Java

LLM APIs

Job description

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.

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