Note: The job is a remote job and is open to candidates in USA. Fifth Third Bank is a financial institution seeking a Lead AWS AI Platform Engineer to advance secure, governed, and scalable enterprise AI and machine learning capabilities. The role architects and maintains AWS-based AI platforms, enables GenAI and AI/ML services, establishes governance standards, and partners with cross-functional teams to support experimentation, production readiness, and responsible AI adoption.
Responsibilities
- 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, SageMaker, 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 capabilities and technical solutions aligned with enterprise AI strategy and business priorities
- Stay current with emerging AI/ML technologies, cloud platform services, architectural trends, and industry best practices to continuously evolve the Bank’s AI enablement ecosystem
- 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
Skills
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, Mathematics, or a related technical discipline
- 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, DevOps/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, SageMaker, Lex, Lambda, API Gateway, S3, IAM, CloudWatch, and related cloud platform capabilities
- Proficiency in Infrastructure as Code (IaC), CI/CD automation, and DevOps practices using tools such as Terraform, Jenkins, CloudFormation, GitHub, or similar platform engineering technologies
- Strong programming and scripting skills with proficiency in Python and familiarity with SQL, APIs, automation scripting, and cloud integration patterns
- Experience enabling Generative AI capabilities including prompt engineering, Retrieval-Augmented Generation (RAG), model orchestration, evaluation frameworks, tool integration, and agentic AI enablement patterns
- Knowledge of AI orchestration and frameworks 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 related to cloud and AI platform operations
- Experience supporting AI/ML experimentation, proof of concepts (POCs), and platform enablement activities within controlled enterprise environments
- Working knowledge of machine learning concepts, model lifecycle management, observability, and AI evaluation methodologies supporting responsible AI adoption
- Proficiency with version control systems (Git/GitHub)
- Understanding of CI/CD pipelines and DevOps practices
- Experience with containerization and Infrastructure as Code (Docker, Terraform)
- Knowledge of data structures, algorithms, and software design principles
- Experience designing observability systems for AI applications
- Collaborates effectively with peers and cross-functional teams
- Applies sound judgment and resolves issues using established guidelines
- Excellent written and verbal communication skills
- Strong analytical thinking and problem-solving abilities
- Ability to manage time effectively and prioritize competing demands
- Self-motivated with demonstrated capacity to work independently
- Experience working in Agile environments
- Proficiency with Microsoft Office suite (Word, Excel, PowerPoint)
- Understanding of ethical considerations in AI deployment
- Position not available for immigration sponsorship
- Advanced degree preferred but not required
Benefits
- Eligible to participate in an incentive compensation plan, with payment based upon company, line of business and/or individual performance
Company Overview