AI Platform Developer Specialist
FNZ is a global wealth management platform provider.
Projects
About FNZ
FNZ describes itself as 'wealth's growth platform', providing a global, end-to-end wealth management platform that integrates modern technology, business operations, and investment operations within a regulated financial institution connected to a universe of investment products. The company serves banks, wealth managers, insurance companies, and asset managers, with over US$2.5 trillion in assets on platform and nearly 30 million end investors served through its clients. Its offerings span wealth management platforms, advisor tools and productivity solutions, asset management distribution, and trade and post-trade securities services, along with a data platform combining an Operational Data Store, Analytical Data Warehouse, and Aggregated Data Warehouse to power analytics, machine learning, and generative AI insights. FNZ has notable clients including Santander, Colonial First State (CFS), Vanguard, Aviva, and Swedbank, and in 2025 announced a global five-year strategic partnership with Microsoft to integrate Azure AI Foundry, Microsoft Fabric, GitHub Copilot, and Microsoft 365 Copilot across its platform and operations. FNZ is backed by major institutional shareholders including Caisse de dépôt et placement du Québec (CDPQ), CPP Investments, Generation Investment Management, and Motive Partners.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build, maintain, and improve reusable cloud infrastructure and platform capabilities for AI and cloud services. You will operate AI infrastructure, CI/CD pipelines, observability, security controls, and cost-governance tooling. You will help product teams deploy services through standardized self-service patterns, support AI model lifecycles, and resolve production issues.
Requirements
- Bachelor’s degree or higher
- Experience deploying and operating LLM-based solutions in Azure or another major cloud provider
- Experience with Model Context Protocol
- Familiarity with AI gateways, model routing, and model-management platforms
- Experience implementing RAG solutions, including vector databases, caching strategies, and retrieval pipelines
- Understanding of agent orchestration frameworks
- Knowledge of AI security and governance controls
- Experience implementing data residency and regulatory compliance requirements
- Experience building reusable platforms, developer self-service capabilities, and golden-path architectures
- Experience developing Terraform modules, providers, or reusable infrastructure frameworks
- Experience with HashiCorp Vault, Key Vault, or equivalent secret-management technologies
- Terraform and Infrastructure as Code
- Kubernetes production operations and troubleshooting
- GitHub and GitHub Actions
- OpenTelemetry and distributed tracing
- Monitoring and logging platforms
- LLM, RAG, and MCP
Responsibilities
- Design, develop, and maintain reusable cloud infrastructure and platform capabilities using Terraform, Azure, Kubernetes, and Infrastructure-as-Code practices
- Implement and operate AI infrastructure services, including Azure AI Foundry, LLM platforms, MCP gateways, RAG solutions, vector databases, storage, and caching
- Build, maintain, and optimize CI/CD pipelines, automation frameworks, and deployment processes
- Enable product teams to deploy and consume AI and cloud services through standardized platform patterns and self-service capabilities
- Implement security, identity, access control, data-governance, and compliance controls for cloud and AI workloads
- Establish observability, monitoring, distributed tracing, logging, and usage instrumentation
- Drive FinOps and cost-optimization initiatives through monitoring, reporting, and governance controls
- Support AI service and model lifecycle management, including onboarding, upgrades, deprecation planning, and rollouts
- Provide escalation support for AI-related production queries
- Assist product teams with infrastructure configuration, deployment, usage instrumentation, access controls, and approval evidence
Benefits
- Flexible and agile working arrangements that meet business and personal circumstances