AI Platform Engineer (Senior / Principal)

What does success look like in this role?

• Design, build, and operate reusable cloud platform capabilities using Infrastructure as Code, CI/CD, containers, Kubernetes, identity services, and cloud networking.
• Develop shared AI platform services including model gateways, API gateways, inference routing, vector and retrieval services, evaluation pipelines, and policy enforcement capabilities.
• Build highly reliable platform services with clear Service Level Objectives (SLOs), observability, tracing, monitoring, automated recovery, and operational excellence.
• Design secure platform foundations that incorporate identity, secrets management, network security, data boundaries, auditability, governance, and controlled access to AI models and enterprise tools.
• Treat the platform as a product by creating reusable APIs, templates, documentation, paved roads, and self-service capabilities that accelerate adoption across engineering teams.
• Optimize platform performance, scalability, and cost through intelligent routing, caching, quotas, lifecycle management, versioning, and cloud resource optimization.
• Establish operational standards for AI platform reliability, incident response, capacity planning, and continuous improvement.
• Mentor engineers, lead architecture discussions, and contribute reusable capabilities that strengthen both client platforms and RAVL's AI engineering practice.
• Partner with engineering, infrastructure, security, architecture, and client stakeholders to deliver scalable AI platform capabilities aligned with enterprise governance requirements.

• Sounds great, but do my skills fit?
• We're looking for platform engineers with deep cloud infrastructure expertise and practical experience building modern AI-enabled platforms.

Required

• Strong experience designing and operating cloud platforms using Infrastructure as Code, Kubernetes, containers, and modern cloud-native architecture.
• Deep experience building CI/CD pipelines, cloud networking, identity and access management, observability platforms, and site reliability engineering practices.
• Experience designing highly available distributed systems with strong operational practices including SLOs, monitoring, tracing, incident response, and capacity planning.
• Working knowledge of large language models, AI inference, agent architectures, and how to expose AI capabilities safely as reusable platform services.
• Experience implementing secure data governance practices including privacy, lineage, lifecycle management, access controls, and scalable data processing.
• Strong understanding of enterprise security, governance, cloud operations, and cost optimization within regulated environments.
• Experience collaborating across engineering, platform, infrastructure, security, and architecture teams to deliver scalable shared services.
• For Senior and Principal candidates, demonstrated experience leading platform architecture, establishing engineering standards, mentoring engineers, and driving adoption of enterprise platform capabilities.

Nice to Have Skills

• Experience with Azure AI Foundry, Azure OpenAI, AWS Bedrock, Vertex AI, or other managed AI platforms.
• Experience with service mesh technologies, API management platforms, GPU infrastructure, model serving frameworks, or vector databases.
• Experience implementing policy-as-code, multi-tenant platform architectures, software supply chain security, or advanced FinOps practices.
• Experience operating enterprise Kubernetes platforms at scale.
• Cloud architecture, Kubernetes (CKA/CKAD), or related certifications.
• Experience working within banking, insurance, wealth management, or other regulated industries.

Mindset Traits

• You enjoy building platforms that enable others to move faster and safer.
• You think in systems and design for long-term scalability, resilience, and operational excellence.
• You balance engineering quality, security, reliability, and cost when making architectural decisions.
• You communicate effectively across engineering, infrastructure, security, and executive stakeholders.
• You enjoy solving complex platform challenges through thoughtful engineering and automation.
• You mentor others and create reusable capabilities that raise the bar across engineering teams.
• You're excited about shaping the future of enterprise AI infrastructure and platform engineering.

Why join RAVL?

• Work alongside experienced consultants solving meaningful, enterprise-scale challenges.
• Help build the AI platforms that power the next generation of enterprise software delivery.
• Flexible, client-aligned hybrid work model—autonomy with accountability, adapting to client delivery needs.
• Variable bonus & RRSP contributions tied to performance and delivery impact.
• 4 weeks paid time off (plus public holidays).
• Paid professional development days and continuous learning opportunities.
• Comprehensive health & dental coverage, including mental health support.
• Commitment to lifelong learning through mentorship, certifications, and continuous improvement.