Member of Technical Staff

About the Role

Ditto is building the agentic social network — where AI agents don’t just assist users, they run the system: understanding people, making decisions, learning from outcomes, and continuously improving how humans meet in the real world.

This is not a traditional full-stack role.

We are looking for engineers who want to build systems where AI is the execution layer and humans design, guide, and govern those systems.

In this role, you will help bring Ditto’s autonomous matchmaking and engagement engine to life. You will build both customer-facing experiences powered by agents and the internal tooling that allows humans and AI to observe, debug, and improve those agents. You will collaborate closely with product, research, and infrastructure to shape the core of Ditto’s agentic platform.

In This Role, You Will

Build agent-driven product flows across matching, chat, scheduling, and re-engagement

Own customer-facing social experiences powered by autonomous AI systems

Design and implement AI-orchestrated pipelines that replace manual workflows

Create internal tools for humans and AIs to:

inspect system state

debug agent behavior

evaluate outcomes

steer system direction

Implement feedback loops connecting:

user behavior

agent decisions

real-world outcomes (matches, replies, dates, retention)

Optimize the system for reliability, speed, and scale

How You Will Work

You will operate as a manager of AI agents .

Your job is not to write every line of code — it is to:

Define what agents should do

Provide the right context

Design the tools they use

Validate their outputs

Build the infrastructure that lets them learn from experience

You will continuously turn:

Human workflows → Autonomous systems → Measurable outcomes

What We’re Looking For

We are looking for engineers who think in systems, loops, and leverage, not just features.

You should:

Have built real production systems

Be comfortable across frontend, backend, and AI

Understand stateful and autonomous systems

Be excited by AI as the execution layer , not just an API

Your background likely includes

Strong TypeScript and/or Python with modern web frameworks (React, Next.js, etc.)

Experience building backend systems (Node, Bun, NestJS, FastAPI, or similar)

Experience with event-driven or distributed systems (RabbitMQ, queues, workers)

Experience with stateful systems (Redis, MongoDB, or similar)

Exposure to LLM pipelines, agents, or orchestration frameworks (LangGraph, LangChain, custom agents, etc.)

Experience with A/B testing, experimentation, or growth loops

Experience building autonomous or AI-driven workflows

Experience with observability, logging, and debugging of AI systems

A mindset of:

shipping fast

measuring real outcomes

iterating based on data

Bonus (not required)

Experience with reinforcement learning, evaluation, or ranking systems

About Ditto

Ditto is reimagining how people meet — starting with dating.

We’re building the first fully agentic social platform, where AI does the heavy lifting: understanding preferences, finding compatible matches, and even setting up real-world dates.

Our co-founders dropped out of UC Berkeley to build this vision. Since then, Ditto has gone viral across campuses, set up tens of thousands of real dates, and raised funding from Google and top-tier VCs, alongside engineers and researchers from MIT, Stanford, Berkeley, and DeepMind.

Dating is just the beginning.

We are building the operating system for human connection — and rewriting how people meet, interact, and form relationships in an AI-native world.

If that excites you, come build with us.