Lead AWS Platform Engineer

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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. This role architects, implements, and maintains AI enablement platforms and services that support rapid experimentation, proof of concepts (POCs), model development, and enterprise adoption of GenAI and AI/ML solutions. The role partners closely with cross‑functional business, engineering, risk, security, and infrastructure teams to establish reusable frameworks, architectural patterns, governance standards, and best practices for responsible AI delivery.

The role is accountable for enabling AI services, maintaining cloud and platform environments, supporting structured and unstructured data integrations, and driving innovation through experimentation, technical exploration, and emerging technology evaluations. Responsibilities include designing scalable AI architectures, supporting platform modernization, creating reusable enablement capabilities, and ensuring alignment with enterprise technology strategy, operational resiliency, and regulatory requirements.

Responsible and accountable for risk by openly exchanging ideas and opinions, elevating concerns, and consistently following policies and procedures as defined. Ensures AI solutions and platforms operate within the Bank’s governance, security, and risk management standards while promoting responsible and ethical AI adoption.

• Enable, architect, and support secure, governed, and scalable AI/GenAI platform capabilities that accelerate enterprise AI adoption across the Bank.
• 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 including 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.
• Stay current with emerging AI/ML technologies, AWS cloud technologies frameworks, and methodologies.
• Contribute to establishing best practices for AI exploration and deployment.

• 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.
• Develop evaluation and governance frameworks to support model validation, responsible AI usage, monitoring, observability, and output quality assessments.
• Collaborate with agile squads, platform engineering teams, and product stakeholders to deliver enabling…