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.
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
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
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
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
Experience with reinforcement learning, evaluation, or ranking systems
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.
Job details are sourced from the employer's original posting.
Open job postingAbout the company
Ditto automatically connects devices in ad-hoc mesh networks to prevent downtime for critical applications, syncing data peer-to-peer without relying on the internet or network hardware. Drive consistent revenue at the edge without WiFi, Servers, or Cloud. Sell a product, deliver a service, and conduct operations anywhere without worrying about connectivity.