Staff DevOps Developer

Visier; Vancouver; On-site; CAD 150,000 - 190,000; Full time

Job summary

Visier is building a centralized control and data plane for our AI transformation. As the Staff DevOps Developer you will own the platform and integration layer, design multi-cloud infrastructure (AWS and Azure), write production-grade Python, and build MCP/RAG services for reliable AI tooling. You’ll enforce security, scale pipelines, and define platform standards while delivering robust, observable operations across environments.

Qualifications

• 7+ years of professional software development and platform/DevOps engineering experience.
• Bachelor’s degree in CS or Software Engineering is preferred.

Responsibilities

• Own the platform and integration layer that the system runs on.
• Define cloud infrastructure design across AWS and Azure.
• Write production-grade Python application code and build API integrations.
• Develop MCP servers and RAG retrieval services for governed agent access.
• Own IaC and CI/CD pipelines to deploy platform services and data artifacts.
• Implement security controls: least-privilege IAM, secrets management, network segmentation, and observability.

Skills

Python production code

Cloud architecture

IaC

CI/CD

Security best practices

Multi-cloud (AWS/Azure)

Terraform

Kubernetes

Docker

Monitoring & observability

IAM & least privilege

Education

Bachelor’s in CS or Software Engineering

Tools

Docker

Kubernetes

Terraform

Jenkins

Bitbucket

Artifactory

Job description

• 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 DevOps 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, ServiceNow, 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, GitHub Actions)
• Education & Experience: 7+ years of professional software development and platform/DevOps 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)