Lead AWS Platform Engineer

Fifth Third Bank • Cincinnati, OH

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About The Position

The Lead AWS Platform Engineer enables and advances enterprise AI and machine learning capabilities within a secure, governed, and scalable technology environment at Fifth Third Bank. The role architects, implements, and maintains AI enablement platforms and services for experimentation, proof of concepts, model development, and enterprise adoption of generative AI and AI/ML solutions. It partners with business, engineering, risk, security, data, and infrastructure teams to establish reusable frameworks, architectural patterns, governance standards, and responsible AI practices.

The position provisions and maintains AWS-based AI platform infrastructure and shared services, supports structured and unstructured data integrations, and evaluates emerging technologies. It establishes platform standards and operational practices that align with enterprise technology strategy, resiliency, security, risk management, and regulatory requirements. The role also creates technical documentation and governance artifacts, conducts technology evaluations, and delivers platform capabilities for product areas and strategic initiatives.

The position is based in Cincinnati, Ohio. It is not available for immigration sponsorship. Compensation includes base salary determined by factors such as relevant skills, experience, education, and location, with eligibility for an incentive compensation plan. Fifth Third describes its benefits as comprehensive and intended to support employees’ physical, financial, emotional, and social well-being; specific benefits are not listed in the posting.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, Mathematics, or a related technical discipline.
• At least 6 years of experience in cloud platform engineering, AI/ML enablement, platform architecture, or enterprise technology solution delivery in 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 services, infrastructure automation, DevOps/IaC practices, and platform enablement frameworks for scalable AI and data solutions.
• Experience collaborating with 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, including provisioning, configuration, automation, monitoring, and operational support.
• Experience with AWS AI/ML and GenAI services such as Amazon Bedrock, SageMaker, Lex, Lambda, API Gateway, S3, IAM, and CloudWatch.
• Proficiency in Infrastructure as Code, CI/CD automation, and DevOps practices using tools such as Terraform, Jenkins, CloudFormation, or GitHub, or similar technologies.
• Strong programming and scripting skills, including Python, and familiarity with SQL, APIs, automation scripting, and cloud integration patterns.
• Experience enabling generative AI capabilities, including prompt engineering, Retrieval-Augmented Generation, model orchestration, evaluation frameworks, tool integration, and agentic AI patterns.
• Knowledge of AI orchestration frameworks and technologies such as LangChain, LlamaIndex, MCPs, vector databases, and enterprise AI integration architectures.
• Experience designing reusable frameworks, reference architectures, guardrails, and operational standards for secure and governed AI platform enablement.
• Familiarity with enterprise security, risk, governance, access management, and compliance considerations for cloud and AI platform operations.
• Experience supporting AI/ML experimentation, proof of concepts, and platform enablement in controlled enterprise environments.
• Working knowledge of machine learning concepts, model lifecycle management, observability, and AI evaluation methodologies.
• Proficiency with version control systems such as Git/GitHub; understanding of CI/CD pipelines and DevOps practices.
• Experience with containerization and Infrastructure as Code, including Docker and Terraform.
• Knowledge of data structures, algorithms, and software design principles.
• Experience designing observability systems for AI applications.
• Effective collaboration, sound judgment, issue resolution, strong written and verbal communication, analytical and problem-solving abilities, time management, and prioritization.
• Self-motivation and demonstrated ability to work independently.
• Experience working in Agile environments.
• Proficiency with Microsoft Office, including Word, Excel, and PowerPoint.
• Understanding of ethical considerations in AI deployment.
• Must not require immigration sponsorship for this position.

Nice To Haves

• An advanced degree is preferred but not required.

Responsibilities

• Enable, architect, and support secure, governed, scalable AI and generative AI platform capabilities across the Bank.
• Design, implement, and maintain AI enablement environments, services, frameworks, and reusable architectural patterns for experimentation, proof of concepts, and production readiness.
• Architect, provision, and maintain AWS AI platform infrastructure and shared services using Infrastructure as Code, automation pipelines, and cloud engineering best practices.
• Enable and support AWS AI/ML and cloud-native services, including Amazon Bedrock, SageMaker, S3, Lambda, and API Gateway.
• Partner with 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.
• Establish and maintain AI platform standards, reference architectures, guardrails, and best practices for secure and responsible AI development and deployment.
• Support the integration of structured and unstructured data sources, cloud-native AI services, APIs, and enterprise platforms.
• Create and maintain technical documentation, architectural guidance, operational procedures, and governance artifacts.
• Lead technical exploration, innovation initiatives, and technology evaluations to improve platform capabilities, developer experience, scalability, and operational efficiency.
• Develop evaluation and governance frameworks for model validation, responsible AI usage, monitoring, observability, and output quality assessment.
• Collaborate with agile squads, platform engineering teams, and product stakeholders to deliver capabilities aligned with enterprise AI strategy and business priorities.
• Deliver platform enablement and technical capabilities for defined product areas or strategic initiatives while maintaining ownership and operational accountability.
• Stay current with emerging AI/ML and AWS technologies, architectural trends, frameworks, methodologies, and industry best practices.
• Contribute to best practices for AI exploration and deployment.

Benefits

• Comprehensive benefits programs intended to support employees’ physical, financial, emotional, and social well-being.
• Eligibility to participate in an incentive compensation plan, with payments based on company, line-of-business, and/or individual performance.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior