Jobs / Planview
Staff Platform Engineer (CloudOps, DevSecOps, Data Foundations)
Planview · Vancouver, BC, Canada
Vancouver, BC, CanadaExp: 8-12 yrs150,000-175,000 CAD/yearlyHybrid
Remuneration
150,000-175,000 CAD/yearly
Location
Vancouver, BC, Canada
Visa sponsorship
Not specified
Job summary
Planview is seeking a Staff Platform Engineer to drive the future of connected work, focusing on GenAI-First Infrastructure, Data Fabric & Foundations, and Cloud & Infrastructure-as-Code. This role involves leading technical initiatives, mentoring engineers, and shaping platform culture to accelerate organizational achievements.
Qualifications
- 8–12+ years in platform engineering, DevOps, SRE, Cloud, Data Platform, AI/MLOps, or infrastructure roles.
- Deep AWS expertise, including multi-region architectures and cloud-native services.
- Terraform mastery, including design patterns at scale, infrastructure testing, and policy-as-code.
- Ability to architect GitOps, multi-cluster, and deployment pipelines using Kubernetes and CI/CD.
- Experience with BCDR strategies.
- Proficiency in ShiftLeft Mental Model on DevSecOps framework.
- Expertise in observability and resiliency.
- GenAI depth, including experience with GitHub Copilot or Claude Code, built/operated MCP servers, understanding of AI-DLC, and spec-driven development.
- Data lakehouse experience, having designed or operated Snowflake/Delta/Iceberg systems with governance.
- Strong architectural thinking, including defining patterns, conducting threat models, creating ADRs, and evaluating tradeoffs.
- Proven cross-functional influence to align teams around platform decisions.
Responsibilities
- Drive GenAI-First Infrastructure, including AI-DLC control plane for model versioning, prompt governance, cost attribution, and evaluation frameworks.
- Build secure, spec-driven Model Context Protocol servers and governance.
- Develop knowledge and context systems, including context graphs, vector stores, RAG pipelines, and memory systems.
- Orchestrate agents with control planes and human-in-loop workflows (e.g., n8n, LangChain patterns).
- Implement AI observability with cost models, token efficiency, and agent health SLOs.
- Understand Data Fabric & Foundations, including data lakehouse architecture (Snowflake, Delta, Iceberg, LakeFormation).
- Manage data governance, including lineage tracking, cost attribution, and quality gates.
- Implement federated systems for multi-region, multi-cloud data sync and API integration.
- Work with polyglot data systems: Kafka, SQL, NoSQL, graph databases, warehouses, and lakes.
- Expertly manage Cloud & Infrastructure-as-Code, including AWS architecture (EC2, Lambda, RDS, EKS, VPC, VPN) and multi-region strategies.
- Utilize Terraform, CloudFormation, and CDK at scale for reusable, testable, policy-enforced modules.
- Architect Kubernetes for multi-cluster, service-mesh, gateway API/ingress, workload isolation, and cost optimization.
- Design CI/CD using GitHub Actions, ArgoCD, and GitOps for diverse workloads.
- Master observability with Datadog, Grafana, Sumo, OTEL, SLOs, meaningful alerts, and cost tracking.
- Lead technical hiring and team composition decisions.
- Mentor engineers and uplift knowledge density; shape platform culture and advocate for best practices.
- Author architecture decisions (ADRs) to guide future choices.
- Drive platform automation to reduce toil by 20–30%.
Skills
AnsibleArgo CDAWSAzureAWS CDKCloudFormationDatabricksDatadogEKSGCPGitHubGitHub ActionsGrafanaKafkaKubernetesAWS LambdaOpenTelemetrySnowflakeSnykTerraform
Relocation
No