Lead AWS Platform Engineer

Overview

The Lead AWS AI Platform Engineer is responsible for enabling and advancing enterprise AI and machine learning capabilities within a secure, governed, and scalable technology environment across the Bank.

• Enable, architect, and support secure, governed, and scalable AI/GenAI platform capabilities that accelerate enterprise AI adoption.
• Design, implement, and maintain AI enablement environments, services, frameworks, and reusable architectural patterns to support rapid experimentation, proof of concepts (POCs), and production readiness.
• Architect, provision, and maintain AWS cloud‑based AI platform infrastructure and shared services using Infrastructure as Code (IaC), automation pipelines, and cloud engineering best practices to ensure scalability, resiliency, and operational efficiency.
• Enable and support AWS AI/ML and cloud‑native services such as Amazon Bedrock, Sage Maker, S3, Lambda, API Gateway, and related platform capabilities within secure and governed enterprise environments.
• Partner with cross‑functional teams (engineering, infrastructure, security, risk, data, and business stakeholders) to onboard and enable AI solutions aligned with enterprise governance and technology standards.
• Evaluate, enable, and operationalize emerging AI/ML and generative AI technologies, services, and platforms for enterprise use cases and strategic initiatives.
• Establish and maintain AI platform standards, reference architectures, guardrails, and best practices for secure and responsible AI development and deployment.
• Support the enablement and integration of structured and unstructured data sources, cloud‑native AI services, APIs, and enterprise platforms to facilitate scalable AI solution delivery.
• Develop evaluation and governance frameworks to support model validation, responsible AI usage, monitoring, observability, and output quality assessments.
• Create and maintain technical documentation, architectural guidance, operational procedures, and governance artifacts related to AI enablement capabilities and platform services.
• Lead technical exploration, innovation initiatives, and technology evaluations to identify opportunities for improving AI platform capabilities, developer experience, scalability, and operational efficiency.
• Collaborate with agile squads, platform engineering teams, and product stakeholders to deliver enabling capabilities and technical solutions aligned with enterprise AI strategy and business priorities.
• Deliver platform enablement and technical capabilities for defined product areas or strategic initiatives while operating with a high degree of ownership, collaboration, and operational accountability.

• Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, Mathematics, or a related technical discipline (advanced degree preferred).
• 6+ years of experience in cloud platform engineering, AI/ML enablement, platform architecture, or enterprise technology solution delivery within secure and governed environments.
• Experience enabling, supporting, or operationalizing AI/ML and generative AI platforms, cloud‑native services, and enterprise technology capabilities in AWS environments.
• Hands‑on experience with AWS cloud platform services, infrastructure automation, Dev Ops/IaC practices, and platform enablement frameworks supporting scalable AI and data solutions.
• Experience collaborating with cross‑functional engineering, infrastructure, security, risk, and business teams to deliver enterprise technology and AI enablement capabilities aligned with governance and operational standards.

• Strong understanding of AWS cloud platform engineering concepts, including provisioning, configuration, automation, monitoring, and operational support of scalable cloud‑native environments.
• Experience enabling and supporting AWS AI/ML and GenAI services such as Amazon Bedrock, Sage Maker, Lex, Lambda, API Gateway, S3, IAM, Cloud Watch, and related cloud platform capabilities.
• Proficiency in Infrastructure as Code (IaC), CI/CD automation, and Dev Ops practices using tools such as Terraform, Jenkins, Cloud…