Mindlapse

About the Company

Mindlapse helps cybersecurity leaders cut through the noise and take smarter, faster decisions by transforming governance from static documentation into living, AI-powered insights. Our Mission We align cyber governance with real-world signals — not outdated checklists — so that security becomes a driver of resilience and business performance. Our Vision We believe the future of cyber governance is AI-native, operational by design, and deeply tied to business priorities. It's not about adding more tools — it's about making the right decisions, at the right time, with the right context. Why We Built Mindlapse We're a team of cybersecurity experts, product builders, and engineers united by a common goal: to bring clarity, speed, and strategic impact to risk and compliance. We use artificial intelligence with purpose, transparency, and responsibility — especially where it matters most: in protecting trust.

Listed Jobs

Company Name

Mindlapse

Job Title

Ingénieur·e SRE / DevOps

Job Description

**Job Title** SRE / DevOps Engineer **Role Summary** Design, build, and operate a secure, highly‑available multi‑cloud infrastructure (AWS, GCP, sovereign cloud) for an AI‑driven SaaS Cyber‑GRC platform. Drive architecture decisions, automate provisioning, enforce compliance, and enable developers through a self‑service platform. **Expectations** - 2‑5 years of hands‑on SRE/DevOps or Cloud Engineering experience. - Ability to work autonomously in a small startup team and influence the technical roadmap. - Strong focus on security, cost efficiency (FinOps), and regulatory compliance (ISO 27001, SOC 2, GDPR, DORA, NIS2). - Collaborative mindset with developers, AI specialists, and cybersecurity experts. **Key Responsibilities** - **Infrastructure as Code & Cloud**: Design and maintain Terraform‑based environments across multi‑account, multi‑region landing zones; provision VPC, EKS/ECS, RDS, S3, IAM, and managed services; implement cost‑optimization strategies. - **Kubernetes & Orchestration**: Operate EKS clusters for multi‑tenant SaaS; manage Helm/Kustomize charts, deployment patterns (blue/green, canary), HPA/KEDA autoscaling, NetworkPolicies, and service mesh. - **CI/CD & Automation**: Build GitHub Actions pipelines for front‑end (React/Next.js), back‑end (AdonisJS), and AI micro‑services (Python); integrate testing, linting, SAST/DAST, automated rollbacks, feature flags, and secret management (Vault, AWS Secrets Manager). - **Developer Experience & Platform Engineering**: Create an Internal Developer Platform for self‑service environment provisioning, preview environments, dev containers, and IaC documentation; reduce manual toil through automation. - **Observability & Reliability**: Deploy monitoring (Prometheus/Grafana or Datadog), logging (Loki/CloudWatch), tracing; define SLI/SLO/Error Budgets; implement intelligent alerting, runbooks, blameless post‑mortems, and AIOps enhancements. - **Security & Compliance**: Embed DevSecOps practices (image scanning, OPA/Gatekeeper policies); harden cloud resources per ISO 27001, SOC 2, GDPR; manage RBAC, least‑privilege IAM, encryption, and network segmentation. **Required Skills** - Terraform (IaC) and cloud‑native provisioning. - Production‑grade Kubernetes (EKS/GKE or self‑managed) and Helm/Kustomize. - Deep knowledge of AWS; familiarity with GCP and sovereign clouds (Scaleway/OVH). - CI/CD tooling (GitHub Actions, GitLab CI) and pipeline automation. - Scripting (Bash, Python) and containerization (Docker). - Monitoring/observability stack (Prometheus, Grafana, Datadog, Loki, CloudWatch, distributed tracing). - Secret management (HashiCorp Vault, AWS Secrets Manager). - Cost‑optimization (FinOps) and multi‑cloud architecture. - Security tooling (SAST/DAST, OPA/Gatekeeper, image scanning). - Strong problem‑solving, communication, and teamwork abilities. **Required Education & Certifications** - Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience). - Preferred certifications: AWS Certified Solutions Architect – Associate/Professional, Certified Kubernetes Administrator (CKA), Google Cloud Professional Cloud Architect, or similar.

Paris, France

Hybrid

Junior

25-02-2026

Company Name

Mindlapse

Job Title

Stage AI Engineer (H/F/NB)

Job Description

Job title: AI Engineer Intern (H/F/NB) Role Summary Support the AI engineering team in a SaaS start‑up focused on AI‑driven cybersecurity. Design, develop, and optimize Retrieval‑Augmented Generation (RAG) pipelines, orchestrate agent workflows, manage multi‑LLM routing, and expose AI services via APIs. Evaluate model performance, reduce token costs, mitigate hallucinations, and implement observability and security best practices. Contribute to experimentation documentation and continuous improvement of the AI stack. Expectations - Graduate or advanced student in data science, machine learning, applied mathematics, computer science, or related field. - Demonstrated proactive learning, autonomous problem‑solving, and ability to measure progress (latency, accuracy, cost). - Deliver structured, testable Python code and participate actively in a fast‑moving production environment. Key Responsibilities 1. Build and refine RAG pipelines: ingestion, chunking, embeddings, retrieval, generation. 2. Orchestrate agent workflows: chaining, state management, conditional routing, fallbacks. 3. Manage multi‑provider LLM routing: cost tracking, latency monitoring, fail‑over logic. 4. Develop API endpoints to expose AI services. 5. Implement evaluation frameworks for response quality (fidelity, relevance, context precision). 6. Optimize token usage and inference costs; propose and test cost‑reduction strategies. 7. Develop hallucination mitigation techniques in compliance‑critical scenarios. 8. Conduct comparative benchmarks of models and prompting strategies. 9. Add observability: trace latency, costs, debug information for AI calls. 10. Document technical decisions, experiments, and results. 11. Apply security best practices to protect pipelines and sensitive data. 12. Collaborate with DevOps on Docker, Kubernetes, and CI/CD pipelines for MLOps. Required Skills - Strong Python programming: clean, modular, testable code. - Understanding of RAG and LLM architectures (theory and practical application). - Experience with AI orchestration frameworks (LangChain, LlamaIndex, or equivalent). - Background in NLP: tokenization, NER, entity extraction, classification. - Proficiency with Git, Docker, Kubernetes, Linux environment. - Familiarity with vector databases (Pinecone, Milvus, Weaviate, ChromaDB, etc.). - Knowledge of knowledge graphs & graph databases (Neo4j or equivalent) is a plus. - Experience with fine‑tuning NLP models, Python backend frameworks (FastAPI, Flask) is a plus. - Basic MLOps: deployment, monitoring, CI/CD. - Understanding of cybersecurity or GRC concepts is advantageous but not required. Required Education & Certifications - Current enrollment in a master’s program or engineering school in data science, AI, applied mathematics, or computer science. - No specific certifications required; relevant coursework or projects in machine learning, NLP, or AI engineering will be considered. ---

Paris, France

Hybrid

25-02-2026