The Role
The Senior AI Engineer will lead AI feature development, define data strategy, implement evaluation pipelines, and mentor junior engineers, while collaborating closely with product and engineering teams.
Summary Generated by Built In
About Symbiotic Security
The role – Senior AI Engineer
What you will work on
What success looks like in your first year
Tech Stack & Environment
Your future team
How we work
What we’re looking for
Why join Symbiotic as a Senior AI Engineer?
Compensation & Benefits (Senior)
Hiring process
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.
- 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).
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.
- 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
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.
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
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.
- 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.
💰 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
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
Skills Required
- Strong hands-on experience with LLMs in production
- Solid software engineering background in Python
- Proven ability to design experiments and iterate systematically
- Experience with modern AI tooling (e.g. Bedrock, LangChain)
- Experience with security or developer tools (nice to have)
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Symbiotic Security is an AI coding company that provides a real-time security platform for software developers. It offers an AI code generation agent that embeds security enforcement directly into the workflow, enabling real-time detection and remediation of security vulnerabilities.
.png){kind=logo}
