About the Role
As an AI Platform Engineer, you will transform community best practices and lessons learned from real AI implementations into standardized platform services, SDKs, templates, developer journeys, architectural blueprints, and governance patterns that can be reused across domains. You are passionate about AI and platform engineering, with a focus on governance, security, and scalability. You understand that compliance is necessary for well-designed implementation in a bank. You are a clear communicator, strong collaborator, goal focused, and flexible.
Responsibilities
Drive AI Standardization and Innovation
•Define and maintain AI architecture standards and reference architectures, in line with bank wide standards (e.g., monitoring, networking, security-by-design, privacy, auditability, code quality)
•Prototype and translate emerging AI implementation patterns into enterprise standards
•Collaborate and align regulatory requirements with enterprise architecture, security, risk, data governance, and platform teams
Build Reusable AI Capabilities
•Design and develop shared AI services, cross-cutting concerns (e.g., observability, access management, security, scalability) and platform capabilities
•Build SDKs, accelerators, templates, and reference implementations for ML, agentic AI, and AI System development
Developer Enablement
•Help shape, maintain, and implement the long-term AI engineering DevEx (Developer Experience) across the bank
•Reduce friction for engineering teams building AI applications
•Drive adoption of MAAP (Machine Learning and Artificial Intelligence As a Platform) capabilities across domains
Platform Engineering
•Design scalable cloud-native solutions
•Implement CI/CD pipelines and platform automation
•Develop integrations between AI services, AKS (Azure Kubernetes Service) services, and supporting platforms
Our Tech Stack and Tooling
•Azure Services
•Azure DevOps (Repositories/Pipelines)
•Docker
•AKS (Kubernetes)
•Databricks / Unity Catalog
•VS Code (with Copilot)
•Nexus/Twistlock
Requirements
Platform/Software Engineering
•Strong software engineering background in Python, including knowledge of Design Patterns, coding best practices, packaging and publishing
•System Engineering skills on Azure Services, including networking and IAM (Identity and Access Management) (Entra ID)
•Experience with DevOps best practices, including version control, CI/CD, automated testing, deployment strategies
•Knowledge of reliability engineering (observability, scalability, availability) on Kubernetes utilizing Helm
•ML lifecycle (training, tracking, serving)
•MLOps and LLMOps
•Generative AI
•AI Agents
•RAG (Retrieval-Augmented Generation)
•AI evaluation (e.g., Arize Phoenix, MLflow)
•Observability and monitoring (Grafana, Prometheus, Azure Monitor)
•Prompt engineering
•Security and governance awareness
•DevEx mindset
•Systems thinking
•Architecture modeling
You're good at what you do and possess the required experience to prove it. However, equally as important – you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused – someone who prioritizes customer success in their work. And finally, you're open and borderless – naturally inclusive in how you work with others.
Conditions
Your career with us isn't just a job—it's an adventure with purpose. We offer a dynamic, hybrid-friendly culture that supports your well-being and empowers you to grow. Our Be Well programs are thoughtfully designed to support your financial, mental, physical, and social health. From your very first day, you'll dive into impactful work that powers the systems our customers rely on every day. You'll have access to tools to chart your career path, personalized development goals, and continuous feedback. You'll develop in-demand skills to grow your career, with access to cutting-edge learning opportunities—from certifications with Microsoft, Google, and Amazon to coaching and hands-on experiences.
