Staff Platform Engineer

🕒 il y a 29 jours

🇺🇸 États-Unis – Télétravail

💵 $193 875 - $258 500 / an

⏰ Temps Plein

🔴 Expert

🏗️ Ingénieur Plateforme

👻 Score fantôme 0%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Gravie

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 2013

🏥 Santé

🛡️ Assurance

🤝 B2B

💰 €150 000 000 Private Equity Round - Gravie en 2025-05

Healthcare • Insurance • B2B

Gravie est une entreprise spécialisée dans les solutions d'assurance santé et de prestations qui aide les petites et moyennes entreprises, les courtiers et les employés à accéder et à gérer des prestations de santé plus flexibles et abordables. Ses offres phares incluent Comfort (un plan de santé à financement partiel), Gravie ICHRA (gestion des remboursements des frais médicaux pour les couvertures individuelles), Gravie Pay (assistance pour les coûts liés aux soins de santé) et Gravie Care. L'entreprise se concentre sur la capacité des PME à offrir des couvertures individualisées à moindre coût, tout en simplifiant la gestion des prestations.

Description

• Build golden roads and paved paths using reference implementations, shared libraries, service templates, scaffolding, and pipeline templates • Measure paved-path adoption and time to first success, and improve areas teams route around • Implement the first real production workload with a real team • Build distributed-systems patterns including backend services, event-driven workers, job pipelines, APIs, and relational data models • Partner with Platform Engineering to build, roadmap, and hand off shared infrastructure • Own migration and adoption of existing services onto new paths and retire replaced systems • Participate in cross-team code reviews and production incidents • Define and maintain target-state architecture with owners and decision dates • Own AWS foundations for platform and AI workloads, including accounts, identity, networks, isolation, runtimes, managed data services, tagging, and cost governance • Drive standards adoption through tooling and pipelines • Lead buy/build/reuse decisions for models, frameworks, and vendors • Consolidate overlapping tools and standards and manage sunset paths • Design and build production-grade AI agent systems, multi-agent workflows, orchestration layers, and supporting services • Design retrieval, context, and memory systems with sensitive-data scoping, redaction, and auditing • Develop AI decision-support systems meeting healthcare and regulated-environment accuracy, traceability, and explainability requirements • Build React and TypeScript user experiences for AI capabilities • Establish AI quality-assurance patterns including automated evaluations, regression testing, groundedness checks, and compliance guardrails • Establish a standard way to build, run, evaluate, and operate AI systems • Connect teams, surface duplicated effort, assign unowned decisions, and align cross-team work • Drive communication through writing, demos, and working sessions • Contribute to roadmap and capacity planning • Facilitate collaboration among Engineering, Product, Data, Security, and Infrastructure • Represent technical direction to leadership and carry business context to engineering • Partner with Product to translate ambiguous business problems into architecture • Raise engineering standards through design review, mentorship, and decision records • Partner with Security, Compliance, and Data on AI governance, access control, and data handling

🎯 Exigences

• Eight or more years of software engineering experience, including architecture scope, organization-wide remit, and ownership of complex systems from design through production • Current hands-on coding and code review experience • Experience building internal platform capabilities voluntarily adopted by other teams • Production AI application experience, including evaluation, monitoring, failure handling, guardrails, latency, and cost control • Deep AWS expertise across multi-account organizations, identity and permission boundaries, networking, compute and serverless runtimes, managed data services, managed model services, and cost/tagging governance • Infrastructure as code experience with Terraform, CDK, or both • Track record establishing and driving adoption of architectural foundations and standards • Hands-on experience with agentic software development using AI coding agents • Deep expertise in Python or JVM backend and distributed systems, or React and TypeScript product engineering • Ability to work across the full system • Experience with retrieval, embeddings, context, memory, evaluation, monitoring, or AI agent architectures and workflows • Strong judgment in testing, monitoring, failure handling, privacy, security, access control, and data governance in regulated or audited environments • Experience working with platform or infrastructure teams to deliver organization-wide change • Experience serving as a central technical point across multiple teams without becoming an approval gate • Demonstrated ability to align disagreeing teams and contribute to roadmap and capacity planning • Clear written communication and effective collaboration across technical and non-technical teams • United States work authorization is required; visa sponsorship question is included in the application • Preferred: healthcare, health insurance, or benefits administration experience, including ICHRA, claims, eligibility/enrollment, EDI, or FHIR • Preferred: venture-backed high-growth company experience • Preferred: internal developer platform or developer experience work • Preferred: GitLab CI at scale • Preferred: production observability and LLM observability, including Datadog • Preferred: event-driven and streaming architecture such as Kafka or Flink • Preferred: agent tooling and standards such as Claude Code, MCP, and agent SDKs • Preferred: AI governance or technology radar experience with security or compliance partners

🏖️ Avantages

• Alternative medicine coverage • Flexible PTO • Up to 16 weeks paid parental leave • Paid holidays • 401(k) program • Transportation perks • Education reimbursement • 2 days of paid paw-ternity leave • Standard health and wellness benefits • Equity offered

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