Staff AI Platform Engineer

🕒 vor 20 Tagen

🇪🇸 Spanien – Remote

⏰ Vollzeit

🔴 Experte

🏗️ Plattformingenieur

👻 Geisterscore 10%

Was es bedeutet: die Wahrscheinlichkeit, dass für diese Stelle niemand wirklich einstellt.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Warum dieser Wert:

• Seit 20 Tagen offen.
• Stellen bei diesem Unternehmen werden meist in 43 Tagen besetzt.
• Kein Gehalt angegeben.

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Technosylva

WebsiteLinkedInAlle Stellen

51 - 200 Mitarbeiter

Gegründet 1997

💼 Beratung

🏥 Gesundheitswesen

📦 Logistik

Consulting • Healthcare • Logistics

<Technosylva> ist ein Anbieter von KI-gesteuerter Software zur Minderung von Waldbrand- und Extremwetterrisiken, die Echtzeitvorhersagen, prädiktive Simulationen und Werkzeuge für das Vorfallmanagement für Stromversorger, Feuerwehren und Versicherungen bereitstellt. Ihre cloudbasierten Produkte (Wildfire Analyst, Tactical Analyst, fiResponse) bieten Situationsbewusstsein, operative Entscheidungsunterstützung und Risikobewertung, um Kunden bei der Planung, dem Betrieb und der Reaktion auf Waldbrand- und Unwetterereignisse zu unterstützen.

Beschreibung

• Own the AI Platform architecture and set its technical vision and standards • Document the architecture • Lead the evolution of the AI gateway and model-routing decisions, including provider routing, hybrid and on-prem routing, failover, caching, rate limits and multi-provider compatibility • Decide the agent orchestration stack • Design sandboxing and lifecycle management for agents that run code or access internal systems • Define multi-agent and human-in-the-loop patterns • Design identity and access control for people and non-human agent identities • Lead model, tool and MCP allowlists and access tiers • Work with Legal and Security on EU AI Act and data-classification requirements • Shape the skills/plugins repository and define the security model for the curated MCP registry • Standardize tooling for tracing agent decisions, evaluations, drift detection and quality-regression monitoring • Design cost attribution and allocation for token and compute spend • Serve as technical escalation point for embedded AI delivery • Unblock teams, review designs and create golden paths • Partner with Security teams on threat modelling and controls for prompt injection, data exfiltration and over-privileged tools • Mentor engineers, run design reviews and RFCs, and represent AI Platform in engineering-wide technical decisions • Participate in on-call rotation and incident response for production AI services

🎯 Anforderungen

• 8+ years in software, platform, infrastructure or SRE engineering • Experience at Staff/Principal level or in a tech-lead role owning architecture across teams • Strong understanding of LLM and API fundamentals, including context windows, tool use, structured outputs, streaming, prompt caching, and provider API differences • Hands-on experience designing or running an LLM gateway or similar layer, including build-vs-buy decisions • Experience with agent orchestration patterns, including multi-agent workflows, delegation, human-in-the-loop approval gates, memory and context management, and token optimization • Experience working with Security teams on threat modelling, security reviews and risk acceptance for production systems • Working knowledge of the Model Context Protocol (MCP), including implementing servers, scoping tools, and reviewing third-party servers for security • Production experience with containers and isolation, including Docker and Kubernetes • Infrastructure as code experience with Terraform or similar on at least one major cloud; Azure preferred • Solid grasp of observability, including OpenTelemetry, Prometheus and Grafana, and reliability engineering for non-deterministic AI systems • Strong coding skills • Record of influencing without authority, writing RFCs and architecture decision records, gaining team agreement, and explaining technical trade-offs to non-technical stakeholders • Nice to have: experience with AI evaluation and observability tools • Nice to have: FinOps experience with usage-based cost models • Nice to have: familiarity with AI governance frameworks including EU AI Act, NIST AI RMF and ISO/IEC 42001 • Nice to have: experience with AI coding agents and extension models • Nice to have: hands-on experience designing or evaluating model routing solutions • Nice to have: experience serving self-hosted or on-prem models • Nice to have: experience building developer platforms, golden paths or internal developer portals

🏖️ Vorteile

• Competitive annual salary • Private health insurance • Flexible benefits plan allowing employees to tailor part of their compensation package to personal needs • Annual bonus based on individual performance and company results • Flexible working hours • Remote work options

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