Senior Full Stack Engineer | AI & Security

Escape Technologies; Paris (TX); Hybrid; USD 85,000 - 101,000; Full time

Benefits offered by this job

Stock Options/BSPCE

Health insurance with Alan

Meal vouchers Swile

EGYM Wellpass

Continuous learning budgets

Premium equipment

Open-source time

Conference attendance

Job summary

Escape Technologies, Paris office, is seeking a Senior Full-Stack Engineer to own the central data model and drive the end-to-end product surface from GraphQL to the UI.

You will work across frontend and backend using TypeScript, GraphQL, Node.js, Prisma, PostgreSQL, and AWS, turning AI research into scalable features for customers.

This is a hybrid role based in Paris with 2 days remote per week; you’ll join a tight-knit engineering team focused on high-impact, low-ego collaboration.

Qualifications

• 5+ years building production web apps with frontend and backend.
• Deep TypeScript knowledge and strong typing.
• Experience designing GraphQL schemas with product focus.
• Excellent communicator and ownership.

Responsibilities

• Own the data model that is the moat: design and evolve schema for assets, findings, and context.
• Turn R&D into product: turn AI output into usable frontend/API/integrations.
• Push PostgreSQL to its edge: index design, pagination, caching, low-latency search.
• Build AI-native workflows: guided triage and remediation surfaces.
• Drive architecture: data modeling, system design, GraphQL schema.

Skills

TypeScript

GraphQL

Frontend development

Backend development

PostgreSQL

AWS

Tools

Svelte

Node.js

Prisma

Kafka

Go

Python

Job description

Senior Full-Stack Engineer (Product & Platform) Paris Office

• Location: Paris (75002), 2 days remote per week
• Company: Escape : Leading AI Cybersecurity
• Compensation: €75–90k base + 0.05% BSPCE depending on seniority and scope
• Total Engineering Team at Escape: 21 Engineers, 4 Technical Leads, 4 Squads

About Escape

Escape is offensive security for the teams that are 100x outnumbered. We build AI agents that find and exploit vulnerabilities in modern applications, APIs, and microservices: the way a real attacker would, but at the speed of a CI pipeline.

We're a Y Combinator W23 company. We just closed an $18M Series A in March 2026 led by Balderton Capital (with Uncorrelated Ventures, IRIS, and YC following on). Our customers and partners include Zoom, Schibsted, Wiz, Pandadoc, and a growing list of teams who've stopped pretending annual pen tests are enough. We're 40 people split between Paris and NYC, scaling to 80 in the next 12 months.

The product surface is real: ASM, business-logic-aware DAST, and AI Pentesting GA-ing this year. The competitive thesis is that LLMs collapsed the cost of offensive engineering by 1000x, and the companies that ship that capability into production first will own the next decade of the category. We're betting we're those companies.

About the Role

In AI, context is the moat. At Escape, the data model is the context: and a team of three owns it end to end.

Every Escape product (ASM, DAST, AI Pentesting) is built on top of one data model rich enough to represent an entire attack surface and everything our agents learn about it. That model is our moat, and this team owns it. You'll own the schema at the heart of the company and the last mile that delivers our offensive R&D to customers through the GraphQL API and the product UI. If it ships to a customer, it goes through your team.

This is not a CRUD SaaS role in security clothing. It's the highest-leverage seat in product engineering: small team, central surface, and a direct line from your commits to what a CISO sees. "Senior" here means you set technical direction, not just execute it.

What You'll Do

• Own the data model that is the moat: Design and evolve the schema representing tens of thousands of assets, millions of findings, multi-identity context, and everything our AI accumulates across engagements. This compounds: get it right and the whole platform gets stronger.

• Turn R&D into Product for customers: Turn the output of our offensive AI research into something teams actually use: through the Svelte frontend, the GraphQL API, integrations, and real-time data refresh. You're the bridge between technology and value.
• Push PostgreSQL to its edge: Query optimization, index design, pagination, caching, low-latency search over millions of records. The platform is intensely data-driven and the standard playbook runs out fast. This is most of the job.
• Build AI-native workflows: Guided triage, assisted remediation, signal extraction from noisy scan data. AI is woven through the product, not bolted on: you build the surfaces where it meets the user.
• Drive architecture: Data modeling, system design, GraphQL schema. You decide how we build, not just what: with a real, un-gimmicky path to Tech Lead.

Our Tech Stack & Focus

Frontend: Svelte + TypeScript, GraphQL client Backend: Node.js, GraphQL (Yoga + Pothos), Prisma, PostgreSQL, Kafka Infra: AWS, GitLab CI, Grafana Adjacent deep tech: Python (AI/ML), Go (network tooling)

Perks & Benefits

• Significant equity (Stock Options/BSPCE) – become a core stakeholder in Escape's journey
• Top-tier health insurance with Alan
• Meal vouchers with Swile
• EGYM Wellpass sport subscription
• Continuous learning: budgets for books and online courses
• Premium equipment to support your work
• Dedicated time for open-source projects
• Present at top international conferences (RSAC, BlackHat, DEFCON, BSides, APIDays)

About You

• 5+ years building production web apps, genuinely strong on both frontend and backend
• Deep TypeScript knowledge: you use the type system to its full potential, you don't just tolerate it
• Proven experience designing (not just consuming) GraphQL schemas A real passion for product, craft, and design: you care how it feels, not only whether it works
• Strong ownership: you fix the problem the moment you spot it Excellent communicator: able to explain technical tradeoffs to non-engineering stakeholders

Nice to have:

• Svelte expertise Security / DevSecOps background Early-stage startup experience