Software Engineer, AI Automation — Business Operations

Simplify; San Francisco (CA); On-site; USD 180,000 - 300,000; Full time

Job summary

Simplify is partnering with a fast-growing AI infrastructure company to hire a Software Engineer, AI Automation in San Francisco. You’ll embed with finance, legal, and people teams, understand how their work gets done, and build software they adopt. Compensation: $224–300K plus equity, plus equity.

You’ll write production code, build intuitive interfaces, and use AI to turn manual decisions and approvals into reliable workflows. Join a team turning research into scalable software.

Qualifications

• Shipped production code in Go, Python, or TypeScript and can learn the needed language.
• Experience with LLM APIs (OpenAI, Anthropic) and agentic frameworks.
• Familiar with AI coding tools (Claude Code, Cursor) and autonomous agents.

Responsibilities

• Design, research, and test AI-driven automation end-to-end.
• Build signals, models, and backtesting infrastructure for AI workflows.
• Work with finance, legal, and people teams to ship usable software.
• Monitor and iterate on live performance as conditions change.
• Collaborate with AI researchers to deploy research quickly.

Skills

Go

Python

TypeScript

LLM APIs

Autonomous agents

System design

Data handling

Tools

OpenAI

Anthropic

Cursor

Claude Code

MCP servers

Agent frameworks

Job description

Most job posts are designed to collect as many applications as possible.

This is not one of them.

At Simplify, we work directly with companies on high‑priority hires.

We’re partnering with a fast‑growing AI infrastructure company to hire a Software Engineer, AI Automation — someone who can embed with finance, legal, and people teams, understand how their work actually gets done, and build software they adopt. The compensation range is $224–300K plus equity.

This is not a traditional business operations or strategy role. You’ll write production code, build intuitive interfaces, and use AI to turn manual decisions and approvals into reliable workflows.

About the company

One‑liner: Building the physical and software infrastructure that brings large‑scale AI compute online.

Stage: A rapidly scaling, private AI infrastructure company with in‑person teams in Austin, New York City, San Francisco, and Seattle.

The company works across data‑center development, construction, and compute operations. As it scales, its finance, legal, and people teams need systems that keep pace with the physical infrastructure being built. This team sits directly beside those experts and turns their knowledge into software.

You won’t be handed a narrowly specified feature. You’ll find the bottleneck, understand the decisions behind it, ship a working product, and improve it with the people who use it.

What you'll work on

• Design, research, and test systematic trading strategies end to end
• Build and improve the signals and models that drive live trading
• Develop the research and backtesting infrastructure needed to evaluate ideas rigorously
• Work with market, alternative, and real‑time datasets
• Take research from hypothesis through validation and into production
• Work directly with engineers and AI researchers to ship research quickly
• Monitor live performance and improve strategies as market conditions change
• Help establish the research culture, methodology, and standards of an early team

What we look for

• You have shipped production code in Go, Python, or TypeScript, and can learn whichever programming language the problem demands.
• You have built features using LLM APIs, including OpenAI, Anthropic, or open‑weight models, MCP servers, and agentic frameworks.
• You work daily with AI coding tools such as Claude Code and Cursor, and use agents to perform useful work autonomously.
• You can identify problems, design solutions, and ship them without waiting for direction or approval.
• You have moved quickly under deadlines while creating foundations that other engineers could extend.
• You have earned credibility with experts outside engineering, such as finance leads, lawyers, recruiters, or auditors, and driven software adoption within their operational deadlines.
• Your shipped products demonstrate product judgment through intuitive interfaces and workflows that match how users work.

Nice to have

• Experience with ERP and fixed asset accounting.
• Experience with financial planning and analysis, cash forecasting, and capital planning.
• Experience with structured finance or treasury operations.
• Experience with contract lifecycle systems.
• Experience integrating applicant tracking systems and human resources information systems, such as Ashby, Greenhouse, Rippling, or Workday.
• Experience with large language model extraction from legal and financial documents.
• Own important products end to end rather than one component of a mature platform
• Work directly with the experts making high‑stakes decisions across a scaling business
• Build AI software that changes how real work gets done—not demos that never leave the lab
• Join an in‑person team that values autonomy, urgency, first‑principles thinking, and work that matters