About Symbiotic Security
Symbiotic Security
is a cybersecurity startup helping developers write secure code through an AI-powered assistant integrated into their IDE and CI/CD pipelines. Our solution has two unique strengths: it provides developers with interactive training to understand vulnerabilities as they code, and it automatically detects and remediates security flaws introduced by generative AI tools such as GitHub Copilot.
➡️ Founded in April 2024
➡️ 24 team members split between
Paris (Tech team)
and
New York (Sales team)
➡️ Goal:
8 new hires by the end of 2026
➡️
Morning Laffitte (Paris 9ᵗʰ)
The role – Senior AI Engineer
We are looking for a
Senior AI Engineer
to
lead and accelerate our AI roadmap
and turn cutting‑edge ideas into robust, production‑ready features inside our developer security platform.
You will be a key member of a small AI team (~2–3 people) and work at the intersection of
LLMs, developer experience, and application security
, with a high level of autonomy and direct impact on the product and roadmap.
What you will work on
Design and own AI features end‑to‑end
that protect code generated by humans and by AI tools (Copilot, etc.), from ideation and prototyping to production and iteration.
Define and drive our data strategy
for AI: dataset definition, synthetic data generation, labelling strategies, and quality control.
Build and improve evaluation and testing pipelines
for our AI assistant so that we can systematically measure quality, regressions, and business impact.
Prototype fast and industrialise selectively
: explore multiple ideas, select the most promising ones, and drive them into production with the engineering team.
Shape our AI architecture and tooling
(prompting strategies, retrieval approaches, memory mechanisms, observability, evaluation frameworks).
Partner closely with
Product, security researchers, and engineering leads
to align AI initiatives with user needs and company priorities.
Mentor more junior engineers
on AI topics and contribute to structuring our AI practice (best practices, documentation, standards).
What success looks like in your first year
3 months
You have a deep understanding of our product, users, and AI stack (Bedrock, LangChain, internal tooling, experimentation environment).
You have delivered at least one
PoC of an AI‑powered protection feature
and significantly improved an existing AI component.
You are seen as a
go‑to person
on AI ideas and trade‑offs.
6 months
You have
industrialised one or more PoCs
end‑to‑end with the engineering team, from prototype to production.
You have set up or redesigned key
evaluation pipelines and quality metrics
for our AI assistant.
You are a
core partner for Product and the CTO
on AI roadmap decisions.
12 months
You are a
reference point for AI topics
in the company and drive complex, cross‑functional projects with high autonomy.
You have materially improved our
time‑to‑market
on AI protection ideas and our overall AI quality.
You actively
mentor others, spread good practices
, and help make Symbiotic a top‑tier place to do applied AI for security.
Tech Stack & Environment
Backend:
Python 3.12+ / Django (monolith, REST API)
Frontend:
TypeScript / React (SPA) for the frontend of the SaaS platform
TypeScript for the IDE plugin
AI stack:
AWS Bedrock, LangChain, LLM proxy, internal observability to monitor latency and quality of AI calls
Database:
PostgreSQL
Architecture:
Monolithic, Hexagonal architecture, DDD being introduced
Cloud:
AWS
Tests:
94% backend coverage, 100% business logic covered
Tools:
Sentry, logs, traces, internal analytics
Satellite services:
CLI tools & AI agents written in Python
Your future team
You’ll work closely with:
Edouard
(CTO)
Salah Eddine
(AI engineer)
Abir & Minh Thang
(Engineering Manager / Tech Lead)
Alexandre, Lucine, Koceila
(fullstack software engineers)
Matthieu
(SRE) and
Anthony
(cybersecurity researcher)
Alexis
(Product Manager) and
Quentin
(Product Designer)
We’re a
multi‑disciplinary, product‑driven team
, not working in silos. AI is considered a
product engineering role
, not a separate research lab.
How we work
Our methodology is a
mix of Scrum and Shape Up
:
2‑week cycles, dailies and retros
Short briefs & kick‑offs
High availability of the EM/CTO for decisions
Strong expectation of
ownership
, even for junior profiles, with support and mentoring
We value:
Curiosity
(especially around AI and new tech)
Product thinking
(understanding the “why”, not just executing the “how”)
Clear communication
on blockers and progress
Comfort with
ambiguity
and evolving priorities
What we’re looking for
Core skills
Strong, hands‑on experience with
LLMs in production
: you have already
built and shipped RAG systems or similar LLM applications
with real users.
Solid software engineering background, ideally in
Python
, with the ability to own complex systems (architecture, performance, reliability).
Proven ability to
design experiments
, choose the right metrics, and iterate systematically.
Experience with
modern AI tooling
(e.g. Bedrock, LangChain or similar frameworks, evaluation stacks, observability for AI systems).
Comfortable working close to the product: clarifying use cases, challenging requirements, and balancing UX, performance, and cost.
Nice to have
Experience with
security, developer tools, or infrastructure / platform products
.
Exposure to
model fine‑tuning or non‑LLM ML
(e.g. ranking, anomaly detection, embeddings, classical ML).
Experience designing or operating
high‑leverage internal platforms
(evaluation infra, experimentation frameworks, data pipelines).
Passionate, has worked with Small Language model, will help the engineering team to evolve.
Background in a
mature AI environment
Strong scientific background (top engineering school or equivalent in maths / CS / applied physics).
Soft skills & mindset
Strong
ownership and leadership
: you identify problems, propose solutions, and drive them to completion, often across teams.
Low‑ego, high‑standards
attitude: you care about impact and quality more than about being right.
Ability to
mentor and uplevel others
, both on AI and engineering topics.
Comfortable working in an environment with
high expectations, fast iteration, and evolving priorities
.
Why join Symbiotic as a Senior AI Engineer?
Huge leverage
in a small AI team (~2–3 people) rather than being a specialist in a large, siloed AI organisation.
A very
multi‑disciplinary role
spanning product, engineering, and security instead of owning a tiny “feature vertical”.
A
diverse technical environment
(security, backend, AI, SRE, product) where you can have real breadth.
Ideal if you want more
substance and scope
than a hyper‑narrow expert role.
Opportunity to shape how we build a
scalable cybersecurity SaaS
powered by AI.
🪴 Strong
career and leadership opportunities
by joining early and helping define our AI practice.
🧑🔬 A
strong product & engineering culture
with high technical ambitions.
🥂 A
vibrant, inclusive culture
with regular team events and offsites.
☝🏽 Direct, visible
impact on the product and on Symbiotic’s trajectory
.
Compensation & Benefits (Senior)
💰 BSPCE (equity) available
🏥 100% health insurance coverage
🍽️ Swile meal card
💻 €500 equipment budget
🚲 Allowance for sustainable commuting (cycling, carpooling, public transport, etc.)
🏖️ RTT + paid vacation
🏡 2 remote days per week
👭 Referral bonus: €2,000
Hiring process
We respect your time and keep the process efficient:
Call with our Talent Acquisition –
Blanche
– 30 minutes
Meeting with our
CTO
– 45 minutes to 1 hour
Case study
to be done at home (async work)
On‑site session with our AI / engineering team (code review and discussion) – ~1.5 hour
Culture fit – lunch with the team – 2 hours
Formal offer