Director, AI Platform Engineering

🕒 vor 1 Monat

🤠 Texas – Remote

🤠 Texas – Remote

💵 $150.700 - $261.800 / Jahr

⏰ Vollzeit

🔴 Experte

🏗️ Plattformingenieur

👻 Geisterscore 16%

Was es bedeutet: wie wahrscheinlich diese Stelle offen bleibt, ohne dass aktiv eingestellt wird.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Wie wir werten: Dauer offen, Neuveröffentlichungen, offene Stellen vs Teamgröße, wie schnell Stellen geschlossen werden, und ob ein Gehalt angegeben ist.Hinweis: eine Schätzung aus öffentlichen Daten, kein Urteil über das Unternehmen. Echte Stellen können hoch punkten, nutze es also als Hinweis, nicht als Fakt.

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BMO

WebsiteLinkedInAlle Stellen

10.000+ Mitarbeiter

🏦 Bankwesen

💸 Finanzen

🔥 Finanzierung im letzten Jahr

💰 €142.900.000 Post IPO debt im 2025-11

Banking • Finance

BMO ist die Bank of Montreal, eine große kanadische Finanzinstitution, die Privat- und Firmenkundengeschäfte in Kanada und den USA anbietet. Der bereitgestellte Websitetext hebt die getrennten kanadischen und US-amerikanischen Bankerfahrungen sowie den zweisprachigen (Englisch/Französisch) Support hervor, was auf eine verbraucherorientierte Bank hinweist, die Privatpersonen und Unternehmen in ganz Nordamerika bedient.

Beschreibung

• Lead the Enterprise AI Platform Engineering function at BMO • Own the AI Gateway, Policy Engine, Identity Fabric, AI Registry, Guardrails Runtime, and AI Observability • Design, ship, and operate control and orchestration infrastructure for enterprise AI workloads • Productionize the developer portal and deliver a federated AI Registry with self-service onboarding and lifecycle workflows • Build policy-as-code infrastructure, policy compilation and GitOps distribution, approval workflows, and policy simulation • Deliver operational, security, and compliance telemetry pipelines with trace correlation and tamper-evident audit evidence • Establish certification workflows, compliance scoring, decommission governance, and evidence generation • Deploy gateway runtime across multiple clouds with policy evaluation, routing, residency, budget/quota controls, and circuit breakers • Deliver a multi-stage Guardrails Runtime covering moderation, prompt-injection defense, PII handling, output validation, hallucination detection, and policy enforcement • Build workload identity, token exchange, trust boundaries, enterprise identity integration, and cross-cloud token federation • Deliver first-year platform capabilities including a production-hardened portal and registry, operational AI Gateway, policy infrastructure, and runtime evidence pipeline • Scale the team from an initial 8–12 FTE through hiring and reallocation of internal engineers • Partner with Security, Architecture, DevOps, domain teams, peer Directors, and senior leadership • Operate what the team builds without a separate run team and design for operability and regulatory defensibility

🎯 Anforderungen

• 8+ years in technical platform, infrastructure, or AI/ML engineering roles in a large enterprise • 4+ years leading and managing engineering teams • Experience building and scaling engineering teams, including workforce planning, hiring, succession planning, and squad structuring • Experience integrating net-new hires with reallocated and seconded internal engineers • Strong mentoring and coaching track record • Experience establishing an inclusive team culture aligned to BMO Values • Experience leading through change and ambiguity • Conflict resolution and cross-team influence • Experience building and operating platform capabilities at scale • Strong knowledge of GenAI platform engineering, including LLM/AI gateways, model routing, RAG, agentic patterns, guardrails, and AI evaluation • Hands-on experience with policy-as-code and authorization systems such as Cedar or OPA/Rego, and GitOps distribution • Experience with workload identity and zero-trust patterns, including SPIFFE/SPIRE, mTLS, token exchange, and federated identity • Strong observability engineering background, including OpenTelemetry, distributed tracing, and telemetry pipelines • Multi-cloud fluency; AWS and Azure preferred • Cloud-native architecture, containerization/Kubernetes, and Infrastructure as Code • Familiarity with Bedrock, Azure OpenAI, SageMaker, Databricks, MLflow, LangChain, or equivalents • Proven CI/CD, DevSecOps, and MLOps/LLMOps delivery experience • Grounding in Responsible AI, AI/data governance, and privacy • Executive-grade communication and relationship management • Strategic and organizational management skills, including roadmap planning, budgeting, forecasting, and vendor engagement • Strong analytical, problem-solving, and prioritization abilities • Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline

🏖️ Vorteile

• Performance-based incentives • Discretionary bonuses • Health insurance • Tuition reimbursement • Accident and life insurance • Retirement savings plans • In-depth training and coaching • Manager support • Network-building opportunities • Tools and resources for professional growth