Director, AI Platform Engineering

🔥 0 minutes ago

🤠 Texas – Remote

🤠 Texas – Remote

💵 $150.7k - $261.8k / year

⏰ Full Time

🔴 Lead

🏗️ Platform Engineer

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BMO

WebsiteLinkedInAll Job Openings

10,000+ employees

🏦 Banking

💸 Finance

🔥 Funding within the last year

💰 $142.9M Post IPO debt on 2025-11

Banking • Finance

BMO is the Bank of Montreal, a major Canadian financial institution that provides retail and commercial banking services in Canada and the United States. The provided site text highlights separate Canadian and U. S. banking experiences and bilingual (English/French) support, indicating a consumer-facing bank serving individuals and businesses across North America.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 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