AI Engineer

Recruiting from Scratch LLC; San Francisco (CA); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Equity included

Health, dental, and vision benefits

Office: Onsite

Job summary

Recruiting from Scratch LLC is building an AI infrastructure platform that provides a unified gateway across 100+ LLM providers. The team works with OpenAI, Anthropic, and other model APIs to deliver a developer-friendly experience and robust interoperability for production AI applications.

This onsite role collaborates closely with founders to shape architecture and product decisions. You’ll contribute to the core gateway, open-source tooling, and developer SDKs, with a strong emphasis on

Qualifications

• 1–2+ years of professional backend or full-stack engineering experience building production systems.
• Experience building APIs and backend services, ideally using FastAPI.
• Hands-on experience with the OpenAI API.
• Understanding of /chat/completions vs /responses and API nuances.

Responsibilities

• Build and maintain the interoperability layer across many LLM APIs.
• Develop transformations between OpenAI/Anthropic specs and native formats.
• Implement provider-agnostic functionality for LLM APIs, including session management and /v1/responses support.
• Design gateway-level systems for features like skills, compaction, batches, and emerging model features.
• Build developer infrastructure via the Python SDK used by millions of users.
• Collaborate across LLMs, MCP, and AI agents to ensure consistent developer experience.
• Support MCP authentication flows and agent use cases.
• Work directly with CEO and CTO on architecture, product and engineering decisions.
• Engage with developers and customers to translate feedback into product improvements.
• Ship quickly and take ownership over implementation and product decisions.

Skills

Backend engineering

Full-stack engineering

API design

OpenAI API

LLM interoperability

Developer tooling

Ownership mindset

User feedback

Tools

FastAPI

Redis

PostgreSQL

Job description

Recruiting from Scratch is a specialized talent firm dedicated to helping companies build exceptional teams. We partner closely with our clients to deeply understand their needs, then connect them with top-tier candidates who are not only highly skilled but also the right fit for the company’s culture and vision. Our mission is simple: place the best people in the right roles to drive long-term success for both clients and candidates.

https://www.recruitingfromscratch.com/

Company Stage of Funding: Early-Stage AI Infrastructure Company

Office Type: Onsite

Company Description

We’re representing an AI infrastructure company building one of the world’s most widely adopted AI gateways. Its platform provides a unified interface across more than 100 LLM providers, giving engineering teams a standardized way to manage model access, routing, authentication, budgets, observability, and governance.

The technology is used by thousands of engineering teams and trusted by organizations including Adobe, Netflix, and NASA. The company is now expanding beyond its core gateway product while continuing to build foundational infrastructure across LLMs, MCP, and AI agents.

This is an opportunity to join a small, highly technical team and work directly with the founders on infrastructure used by developers building production AI applications.

What You Will Do

• Build and maintain the interoperability layer that provides a unified interface across a large number of LLM APIs and providers.
• Develop transformations between OpenAI and Anthropic API specifications and the native formats of other model providers.
• Build provider-agnostic functionality across LLM APIs, including session management and /v1/responses functionality.
• Design gateway-level systems supporting provider capabilities such as skills, compaction, batches, and other emerging model features.
• Build developer infrastructure used by millions of users through the company's Python SDK.
• Work across LLMs, MCP, and AI agents, helping create a consistent developer experience across rapidly evolving ecosystems.
• Support a wide variety of MCP authentication flows and agent use cases.
• Work directly with the CEO and CTO on architecture, product, and engineering decisions.
• Engage directly with developers and customers to understand problems and translate feedback into product improvements.
• Ship quickly and take meaningful ownership over both implementation and product decisions.

Ideal Candidate Background

• 1-2+ years of professional backend or full-stack engineering experience building production systems.
• Experience building APIs and backend services, ideally using technologies such as FastAPI.
• Meaningful hands-on experience working with the OpenAI API.
• Understands the differences between /chat/completions and /responses and can discuss API-specific behavior and implementation nuances.
• Strong understanding of modern LLM APIs and how developers integrate models into production applications.
• Comfortable learning the APIs and behavior of different model providers and translating between them.
• Strong engineering fundamentals around API design, reliability, and production software.
• Comfortable operating with significant ownership on a small engineering team.
• Interested in speaking directly with users and solving real developer problems.
• High level of curiosity and interest in the rapidly evolving AI infrastructure ecosystem.

Preferred

• Experience building LLM infrastructure, AI gateways, or developer tooling.
• Experience working across multiple LLM providers rather than exclusively with a single model API.
• Familiarity with Anthropic's API in addition to OpenAI.
• Experience with MCP and emerging agent infrastructure.
• Experience building or contributing to open-source software.
• Experience maintaining SDKs, APIs, or developer-facing infrastructure with significant external usage.
• Familiarity with Redis and PostgreSQL.
• Experience thinking deeply about developer experience and API ergonomics.
• Comfortable working directly with founders in a fast-moving early-stage environment.

Compensation and Benefits

• Equity included.
• Health, dental, and vision benefits.
• Office: Onsite.
• Core technology stack includes Python, FastAPI, Redis, and PostgreSQL.
• Opportunity to work directly with the CEO and CTO on critical product and infrastructure decisions.
• Significant ownership over products used by thousands of engineering teams.
• Best suited for an engineer excited about LLM APIs, interoperability, developer infrastructure, and open-source software, rather than someone primarily interested in model research or training.