The Opportunity Mercury is QuoIntelligence's Threat
Intelligence platform: it processes over 2 billion signals, tracks
400+ threat actors, and delivers finished intelligence to security
teams across financial services, energy, and government in Europe.
You will join a four-person engineering team, working directly with
the engineering lead on Mercury and Agent Karla , an AI-powered
threat analyst that runs on the Mercury engine. You will ship new
features and pay down tech debt in the same week. The team treats
clean, maintainable code as a prerequisite, not a nice-to-have. If
you want to build a product where what you ship reaches real users
quickly, where you will shape how the engineering team works as it
grows, and where the domain is genuinely interesting, keep reading.
What You'll Do Design, build, and ship backend services in Python:
REST APIs, web services, data processing. This is roughly 60% of
your time. The APIs serve both internal teams and external clients,
so performance and reliability matter. Build and maintain basic
frontend features in React and TypeScript. You will work across the
full stack, not just behind the API layer. Write and maintain tests
at every level: unit, integration, end-to-end (Playwright or
similar). Testing is a first-class concern, not an afterthought.
Own CI/CD pipelines, code quality tooling, and static analysis. You
will have direct influence over how the team ships code. Work with
data: SQL queries, data modeling, domain modeling, and
visualization. Mercury processes threat intelligence data;
understanding how to query and present it well is part of the job.
Collaborate across teams. The top priority for this hire is someone
who asks for help when stuck, proactively helps others, and
communicates clearly with non-engineering stakeholders. AI-First in
Engineering We want AI to be part of QuoIntelligence’s engineering
operating model. We expect engineers to use AI tools like Cursor by
default across design, coding, debugging, testing, and
documentation. This role is not about casually using AI for
convenience. It is about using AI to materially increase speed,
leanness, and impact. You know how to turn AI into engineering
leverage,



shorten delivery cycles, and focus your time on the
highest-value problems. We also expect strong judgment. As a
cybersecurity company, we move fast, but we do not use AI blindly.
You understand the risks of AI-assisted and agentic coding, know
how to validate important outputs, and apply pragmatic safeguards
where they matter most. The best candidates do more than use AI
well themselves. They help re-engineer how the team works by
building repeatable workflows, lightweight standards, and better
tooling that make everyone faster. They can coach teammates who are
less familiar with agentic coding, and act as positive drivers of
AI adoption across the engineering team and beyond. What You'll
Bring Must-haves: AI-assisted development: you actively use AI
tools (e.g. Cursor) in your daily workflow and can evaluate their
output critically Strong Python backend experience: you have
designed and shipped production APIs, web services, and data
processing systems Working familiarity in React and TypeScript: you
can build and maintain basic frontend features, not just read them
Solid testing discipline: unit, integration, and e2e testing are
part of how you work, not something you add when asked CI/CD and
code quality tooling experience: you have set up or maintained
pipelines and care about keeping them healthy Data proficiency:
SQL, data modeling, and enough comfort with data analysis and
visualization to work with intelligence data Clean code habits: you
produce code that the next person/agent can read, maintain, and
extend. You keep things simple. Nice-to-haves: Go or additional
programming languages UX and design principles knowledge Your First
90 Days Month 1 : By day 30, you have a working mental model of
Mercury's architecture: where the data flows, where the pain points
are,



and what you would change first. Month 2 : You own a
significant feature end-to-end, from API design through React UI to
Playwright tests. You have started reshaping something: the CI
pipeline, the test strategy, a slow endpoint, the way the team
reviews code. Your commits are changing how the product works, not
just adding to it. Month 3 : An engineering practice or system that
you built is now part of the team's workflow. You are the go-to
person for at least one area of the codebase. What We Offer Full
ownership from day one . Four engineers, not forty-seven.
Everything you ship is visible in the product. Interesting domain .
Unified Risk Intelligence solution with an AI-agentic product for
enterprise clients across Europe, not another generic SaaS
dashboard. Mercury processes 2B+ signals and turns them into
understandable risks; Agent Karla is a multilingual AI threat
analyst built on top of it. Remote with autonomy . Small team, low
bureaucracy, high trust. Based in Italy or Spain. Shape the
engineering culture. As the team grows, your practices and
decisions become the foundation. AI-native workflow . Cursor is the
standard tool. AI is part of the daily work, not an experiment. FAQ
How small is the engineering team? Four engineers (including the
engineering lead), with adjacent engineering teams. QI has ~40
people total. You grow by taking on harder problems and a broader
scope. The engineers who joined early shaped the systems that the
product runs on today. Do I need cybersecurity experience? No. The
domain is interesting, and you will learn it on the job. What
matters is strong engineering fundamentals and the ability to pick
up new domains quickly. Several QI engineers came from outside of
cybersecurity. What is the tech stack? Python (backend),
React/TypeScript (frontend), Playwright (e2e testing). The product
is Mercury, a SaaS intelligence platform, and Agent Karla, a
conversational agent (based on an agentic infrastructure). Data
pipelines and ML tooling are built by adjacent teams. The Process
Recruiter Interview AI Fluency Interview Team Interview Live Coding
Offer

📌 Senior Software Engineer (m/w/d) (Madrid)
🏢 Quointelligence
📍 Madrid