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
