---
title: 'Member of Technical Staff at Ditto'
canonical: 'https://feeny.ai/job/member-of-technical-staff-ditto-san-francisco-hqkrh4xpmv4s'
type: 'job'
last_seen: '2026-09-12'
---

# Member of Technical Staff at Ditto

- **Company:** Ditto
- **Location:** San Francisco, CA
- **Compensation:** $120k–$300k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-05-27
- **Last confirmed live:** 2026-09-12
- **Apply:** https://jobs.ashbyhq.com/dittoai/c3ecca63-e3e7-4572-afd2-7727b1bfaf3a

## Job description

## 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.

## About Ditto

## Company Overview
- **One-liner**: Ditto is an AI-powered matchmaking platform that pairs college students for in-person dates by simulating interactions between AI agents of user profiles.
- **Entity Type**: Private (Seed stage)
- **Headquarters**: Berkeley, California, United States
- **Founded**: 2024
- **Founders**: Not publicly available

## Core Business
- **Primary industry**: AI-powered Social/Dating Technology
- **Target customers**: B2C — College students (18+) in the United States
- **Mission or purpose statement**: To connect people with the right people through the shortest possible path, using AI agents to simulate interactions and find meaningful matches before users ever meet.

## Products & Services
- **Ditto Matchmaking Platform**: An AI-driven service where users submit their preferences and profile information. Ditto uses frontier LLMs and a multi-agent system (including analysis, matchmaking, and scheduling experts) to simulate conversations between AI agents of user profiles. It then texts users a curated date plan (time, place, and match details) for an in-person coffee date on campus. No swiping or chatting is required.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total Funding — **$10.8M** (Seed Round of $9.2M led by Peak XV Partners in February 2026, preceded by a $1.6M Pre-Seed from Gradient in May 2025)
- **Notable Investors/Partners**: Peak XV Partners (lead, Seed), Gradient (lead, Pre-Seed)
- **Growth Signals**: 
  - Rapid headcount growth: 81 employees with a monthly growth rate of +14.6%
  - Strong web traffic growth: monthly visits of ~139,301 with +84.6% monthly traffic growth
  - 70% of users get their first date within 2 days of signing up (as of a recent system upgrade)
  - Expanding from a select group to broader college campuses

## Competitive Advantages
- **Agentic AI Matchmaking**: Uses frontier LLMs and a multi-agent system to simulate conversations between AI representations of user profiles, identifying compatibility before users meet — a novel approach compared to traditional swipe-based apps.
- **No Swiping or Chatting**: Eliminates the friction of manual browsing and messaging; users simply submit preferences and receive a curated date plan.
- **Safety-First Design**: Only verified students at the same school can match, and only the matched date sees the user's profile, with dates held at on-campus spots.
- **Rapid Matching**: 70% of users get their first date within 2 days of signing up, indicating strong algorithmic efficiency.

## Strategic Focus
- **Agentic Social Network**: Ditto is building toward an "Agentic Social Network" where AI agents represent users, interact, learn, and evolve to find compatible connections — expanding beyond dating to collaborators, co-founders, and soulmates.
- **College Market Penetration**: Currently focused exclusively on college students, with plans to scale to cities and potentially nationwide.
- **Continuous Preference Learning**: The system learns from user feedback after each date to refine future matches, creating a compounding data advantage.

## Why Work Here
- **Cutting-Edge AI Work**: The company is building a multi-agent system using frontier LLMs, agent orchestration, and simulation technology — a compelling environment for engineers interested in applied AI research.
- **High-Growth Trajectory**: With 81 employees and +14.6% monthly headcount growth, the company is scaling rapidly, offering early-stage impact and career growth.
- **Remote/Hybrid Policy**: Not explicitly stated, but the company has offices in Berkeley, CA (HQ) and Leeds, UK, suggesting a distributed team.
- **Engineering Culture**: The tech stack includes Python, TypeScript, React, MongoDB, Redis, RabbitMQ, and Harness, indicating a modern, full-stack engineering environment.
- **Notable Perks**: Working on a product that directly impacts users' social lives; opportunity to shape the architecture of an agentic social network from an early stage.

## Sources
1. [ditto.ai](https://ditto.ai/)
2. [LinkedIn - Ditto](https://www.linkedin.com/company/dittoai)
3. [Ditto Manifesto](https://ditto.ai/manifesto)
4. [Ashby Careers - Ditto](https://jobs.ashbyhq.com/dittoai)

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