Job Description

About Us

Have you ever wanted to build something that doesn't just improve the status quo, but makes it 100x better? Not just a small step forward, but a complete reinvention. That's what we're doing, and we need the best people to help us make it happen.


We're an early-stage start-up out of London working at the intersection of system design, cloud infrastructure, and AI to accelerate the adoption of modern tools and technologies. Our goal is nothing less than to enable businesses of all sizes and shapes to leverage best-of-class technologies and the latest advancements in GenAI -- including agentic frameworks.


We've recently launched the beta version of our product, having raised a hefty pre-seed fund from Tier 1 investors with additional contributions from some brilliant angels to bring the vision to life. We are now in delivery mode and have already partnered with 20+ world-renowned brands to bring the product to market.

Sounds exciting? This is a rare opportunity to join at the earliest stage and help build the foundations of a generational product.

The Role

We're looking for an

AI Engineer

with deep experience in applied sub-fields such as

recommender systems

,

retrieval-augmented generation (RAG)

,

agentic AI

, or

automated decision-making

to drive the development of our core product: Dragonfly's tool stack recommender engine.


This role sits at the intersection of data science, product engineering, and systems design. You'll work closely with our engineers, designer, and leadership team to evolve the intelligence layer of our platform -- shaping models, experimenting with LLMs, building scalable data pipelines, and pushing the boundaries of what's possible with applied AI.

What You'll Be Doing:

Owning and evolving the intelligence layer of our recommender system. Designing and implementing AI/ML systems that scale gracefully. Applying and iterating on LLMs and data-driven approaches to improve recommendations. Rapidly experimenting with RAG, search algorithms, and agentic architectures. Debugging complex model behaviours and improving reliability and observability. Staying on top of the latest research and applying it pragmatically. Collaborating cross-functionally to make complex ideas simple and actionable. Shipping fast, learning faster, and iterating on user and stakeholder feedback.

We Are Looking For Someone Who:

Has hands-on experience with

search and information retrieval

, including BM25, hybrid search, and ranking metrics (nDCG, Reciprocal Rank, etc.). Understands

recommender systems

, from collaborative filtering to modern RAG pipelines. Knows how to design

agentic LLM systems

, balancing cost, latency, and performance. Is familiar with

observability frameworks

such as Langfuse, LangSmith, or OpenTelemetry. Has worked with

knowledge graphs

and

graph databases

. Is comfortable with

MLOps workflows

-- Docker, Kubernetes, CI/CD, and cloud environments. Communicates clearly, collaborates actively, and moves fast without breaking quality. Is curious, pragmatic, and resourceful -- figuring things out even when the path isn't obvious. Has strong opinions about code quality but knows when speed matters.

Our Stack

Our stack is constantly evolving, but here's a flavour of what we're using. We don't expect you to know everything -- but curiosity, adaptability, and the ability to leverage AI tools to learn fast are must-haves.

Core AI & Machine Learning

Python

Vertex AI / Hugging Face / OpenAI APIs

LangChain / BAML

-- LLM frameworks

Langfuse, LangSmith

-- Observability

Pandas, NumPy, scikit-learn, PyTorch

-- Data & ML stack

Data & Infrastructure

BigQuery

-- Cloud data warehouse

PostgreSQL

-- Application data

Pulumi

-- Infrastructure as Code (TypeScript)

Google Cloud Platform (GCP)

-- Cloud provider

GitHub Actions

-- CI/CD

Docker / Kubernetes

-- Containerisation

Cloudflare

-- CDN and DNS

Frontend & Backend

TypeScript

,

Next.js + React

,

Node.js

Tailwind CSS

,

Shadcn UI

,

Radix UI

Why Join Us

This is a ground-floor opportunity to shape not just the product, but the intelligence that powers it. You won't be implementing academic models; you'll be designing real systems that help real businesses make smarter, faster decisions. If you love applying AI pragmatically, moving fast, and building with purpose, this is your playground.


Let's build something people love to use, and something that actually works.

What We Offer

The opportunity to define and shape the AI foundation of a high-potential startup from day one. Creative freedom and a high-trust environment focused on outcomes over process. Direct access to founders and an experienced, mission-driven team. Competitive salary and meaningful equity package. 30 days' annual leave, plus 8 bank holidays. Private health insurance. Hybrid setup with weekly in-person collaboration in London. An intellectually stimulating environment where speed, curiosity, and product delivery are celebrated.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.