- 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)
#J-18808-Ljbffr
Sign in
To continue your applicationor continue with email
By continuing you agree to our Terms & Privacy Policy.
Similar jobs
Show more