Role Description Nous sommes à la recherche d’un·e développeur·euse plateforme senior pour rejoindre notre équipe dynamique et contribuer à la conception et au développement des infrastructures et systèmes backend qui propulsent les produits de nos client·e·s — principalement des organisations du secteur de la santé. Ce poste combine ingénierie produit, travail d’infrastructure et développement d’outils de plateforme afin de livrer des solutions de haute qualité sur des environnements technologiques variés. Dans ce rôle, vous travaillerez directement avec nos client·e·s, intégré·e à des équipes multidisciplinaires composées de designers, de data scientists et de développeur·euse·s. Vous pourriez, selon les projets, être amené·e à diriger certaines initiatives ou, à l’occasion, à travailler de façon autonome avec un·e client·e. Veuillez noter que, bien que nous soyons spécialisés dans le secteur de la santé et les industries réglementées, tous nos projets ne relèvent pas de ces domaines. Vous pourriez donc être amené·e à travailler sur des projets variés dans différents secteurs, selon les besoins. Qualifications - 5+ années d’expérience comme développeur·euse logiciel, ingénieur·e DevOps, SRE et/ou ingénieur·e plateforme. - Solide expérience en développement backend, notamment dans la création d’API, de services et d’intégrations de données. - Expérience avec l’infrastructure infonuagique (AWS de préférence) et avec des outils d’infrastructure as code comme Terraform, CloudFormation ou des équivalents. - Expérience dans la conception, la mise en place et le maintien de pipelines CI/CD et d’automatisations de déploiement. - Excellentes compétences en communication et capacité à expliquer des problèmes techniques complexes de manière accessible. - Adaptabilité, autonomie et aisance dans des environnements dynamiques. Requirements - Concevoir et mettre en œuvre des architectures infonuagiques sur AWS. - Développer de l’infrastructure as code avec Terraform. - Mettre en place des pipelines CI/CD. - Déployer et gérer des services en environnement de production. - Développer des automatisations de déploiement, des suites de tests et des outils de productivité pour les développeur·euse·s. - Recueillir les besoins, échanger avec les parties prenantes, développer de nouvelles fonctionnalités et améliorer les produits logiciels. - Planifier et coordonner les livrables, le périmètre, les échéanciers et les budgets d’une équipe projet. - Proposer des améliorations de processus et d’outillage, accompagner et mentorer des collègues plus juniors. Benefits - Budget pour le bureau à domicile et les équipements. - Budget annuel de développement professionnel. - REER avec contribution de l’employeur après 1 an. - Assurance santé et dentaire payée à 100 % par l’employeur. - Assurance vie et assurance invalidité de courte et de longue durée. - Complément de congé parental (8 semaines) pour les employés ayant plus d'un an d'ancienneté.

• Leverage AI-assisted workflows across the engineering lifecycle • Enable and support Linux-based software platforms • Upgrade, patch, and validate core OS libraries and toolchains • Contribute to cryptography, security, and compliance initiatives • Perform deep system-level debugging across hardware, kernel, build, and user-space layers • Plan, integrate, and validate complex tool chain and dependency changes

Role Description We’re looking for a senior, hands‑on Cloud Platform Engineer to help design, standardise, and operate cloud platforms that underpin multiple AI‑driven products and services. This role is about building well‑defined, reusable platform patterns that enable delivery teams to move quickly while maintaining high standards of reliability, security, and cost control. You’ll play a key role in shaping how AI and cloud services are built, deployed, and operated across several concurrent initiatives, reducing fragmentation and improving consistency across the platform estate. This is a hands‑on technical role for someone who enjoys making strong architectural decisions, establishing clear standards, and balancing flexibility with standardisation in a fast‑moving environment. Qualifications - Strong experience operating AWS‑based platforms in production - Proven expertise with Terraform, including module design and CI/CD integration - Hands‑on experience with container platforms: ECS preferred; EKS acceptable if adaptable - Experience operating API gateways (Kong or equivalent) - Solid understanding of cloud networking, service discovery, and communication patterns - Experience supporting multiple teams or projects on a shared platform - Strong troubleshooting skills and real‑world production operations experience - Practical experience running or supporting AI/ML workloads in production - Strong understanding of scaling characteristics of AI workloads - Familiarity with model serving frameworks, data processing pipelines, AWS managed AI / ML services, GPU workloads or specialised compute environments, feature stores, vector databases, or embedding pipelines, event‑driven architectures, and cloud security best practices (IAM, secrets management, Zero Trust) - Platform engineering or internal developer platform experience Requirements - Design and implement well‑defined architecture patterns for cloud‑native and AI‑enabled services on AWS - Create and maintain reusable blueprints for common service types and workloads - Drive consistency across multiple projects through shared modules, templates, and platform tooling - Define standards for service deployment, integration, communication, and day‑to‑day operations - Build and maintain Terraform‑based infrastructure, with a strong emphasis on modular, reusable design - Define CI/CD patterns for infrastructure provisioning and change management, application and model deployment - Enforce best practices through pipelines and automation, rather than documentation alone - Embed SRE principles across all services, including monitoring, logging, and distributed tracing, SLIs, SLOs, and actionable alerting - Continuously improve reliability, performance, and cost efficiency - Operate and evolve API gateway and data plane technologies (e.g. Kong) Benefits - A competitive salary dependent on experience - A contributory pension scheme - Private healthcare - 25 days annual leave, plus bank holidays and the opportunity to buy or sell holiday - A flexible approach to working hours - Continuous personal development, career path and training - And more... Company Description In 2023, 2024 and 2025 we were recognised as one of the Best Workplaces in Tech by Great Place To Work UK, the global authority on workplace culture.

Role Description - Take full ownership of NeoSigma's platform infrastructure — lead architectural decisions and design tradeoffs from day one. - Build and scale core infrastructure across multi-cloud environments (GCP, AWS, Azure). - Own CI/CD pipelines and deployment automation end-to-end, with strong rollout, rollback, and environment parity. - Architect for security from day one: IAM, secrets management, least-privilege access, encryption, and audit logging baked in by default. - Design and enforce data retention policies — minimal collection, defined TTLs, PII handling — so privacy is structural, not an afterthought. - Build and maintain observability: structured logging, metrics, alerting, and on-call practices. - Lead enterprise deployment architecture — design and ship BYOC and VPC-isolated deployments for regulated enterprise customers. - Own the technical relationship with enterprise customers during deployment: SSO/SAML integration, network configuration, data residency, and compliance documentation (SOC 2, HIPAA, GDPR). Qualifications - 2+ years of backend or infrastructure engineering — we look for slope over intercept. - Shipped real infra at a startup and lived with the consequences. - Strong fundamentals in multi-cloud infra (GCP, AWS, Azure), Kubernetes, and Terraform. - Security-first mindset: blast radius, attack surface, audit trails. - Experience with SQL, object storage, and caching layers for high-throughput workloads. - Familiarity with enterprise deployment patterns: VPC isolation, BYOC, SSO/SAML/SCIM, compliance surface. - High ownership mentality — you see problems through to completion and don't wait for someone else to notice what's broken. - Generalist instincts: comfortable across infra, backend services, data pipelines, and deployment tooling. - Bachelor's degree in CS, Engineering, or related field (or equivalent practical experience). - Genuine interest in AI systems and enthusiasm for building infra that makes agentic products work in production. Benefits - Competitive salary plus meaningful equity package. - Comprehensive medical benefits and generous PTO. - Flexible work arrangements. - Direct impact on company direction and technical decisions. - High ownership and the opportunity to make a career-defining impact.