Staff DevOps Developer Job Vancouver area,BC Canada,Software Development

Visier is building the centralized control and data plane—the infrastructure, pipelines, and governance layer that powers our internal AI transformation (Vector) across professional services, customer success, and internal knowledge.
As the Staff Dev Ops Developer on this initiative, you will own the platform and integration layer that the entire system runs on.
You will define how cloud infrastructure is designed, write production-grade Python application code, and build the Model Context Protocol (MCP) servers and RAG retrieval services that enable AI tools and agents to reliably query and act on organizational knowledge
In this role, you will bring a blend of software engineering discipline, deep cloud networking and Infrastructure as Code (IaC) expertise, and an eye for emerging AI agent architecture.
You will evaluate emerging agent frameworks, set platform-wide engineering standards, and engineer secure, resilient architectures designed to scale
Platform & Network Architecture:
Define and operate a multi-cloud infrastructure across AWS and Azure—specifying compute, storage, VPCs, subnets, private endpoints, and load balancing with clear architectural rationale
Production Python & Integration Layer:
Write tested, maintainable Python application code, build resilient API integrations with core source systems (Salesforce, Service Now, Gong, Gainsight), and develop internal tooling and automation workflows
RAG Context Engine & MCP Servers:
Design, build, and optimize the inference-time retrieval service—from query embedding and vector search to re-ranking—and expose this via Model Context Protocol (MCP) servers for governed agent access
Infrastructure as Code & Modern CI/CD:
Own platform infrastructure using Terraform across environments and establish automated CI/CD pipelines (Jenkins, Bitbucket, Artifactory) to deploy platform services and data pipeline artifacts
AI Tooling & Agent Skill Integration:
Define and lead the integration layer between the data warehouse and AI assistants, developing agent skill definitions, query APIs, and optimized prompt structures for reliable agent execution
AI System Security & Platform Operations:
Embed foundational security controls—secrets management, least-privilege IAM, network segmentation, and defenses against prompt injection—while establishing robust monitoring, cost governance, and observability

Infrastructure as Code & Cloud Operations:
Deep expertise in Terraform (modules, state management, remote backends) and hands‑on operational mastery of AWS and Azure managed services
Production Python Mastery:
Strong command of Python as a primary language, with a history of setting code quality standards, writing clean application logic, and building scalable API integrations
RAG Infrastructure & AI/Agent Awareness:
Practical knowledge of RAG pipelines (vector search, chunking, re-ranking), agent frameworks, tool‑calling interfaces, and AI-specific security risks (e.g., prompt injection, Lethal Trifecta)
Containerization & CI/CD Pipelines:
Production experience designing and operating containerized workloads using Docker and Kubernetes, alongside owning automated CI/CD pipelines (Jenkins, Bitbucket, Git Hub Actions)
Education & Experience:

7+ years of professional software development and platform/Dev Ops engineering experience with a track record of independently owning complex architecture end-to-end; a Bachelor’s degree in CS or Software Engineering is preferred
Cloud Networking & Security Discipline:
Robust understanding of cloud networking (VPCs, routing, security groups, private endpoints, TLS) alongside security practices (OAuth, SAML, Okta, secrets management, and RBAC)

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