VP AI Lead Infrastructure Engineer
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Role details
Tech stack
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Job description
- Applies technical expertise and problem-solving methodologies to projects of moderate scope and executes creative solutions for design, development, and technical troubleshooting for problems of moderate complexity
- Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.
- Drives a workstream or project consisting of one or more infrastructure engineering technologies and works with other platforms to architect and implement changes required to resolve issues and modernize the organization and technology processes
- Strongly considers upstream and downstream data and systems or technical implications and advises on mitigation actions
- Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations.
Requirements
- Formal training or certification on infrastructure engineering concepts and 5+ years applied experience with deep experience on at least one major cloud provider (AWS preferred: compute, networking, IAM, managed Kubernetes, observability).
- Deep knowledge of one or more areas of infrastructure engineering such as: hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience or performance assessments
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Hands-on experience running ML or GenAI workloads in production, such as consuming hosted model APIs (Amazon Bedrock, Azure OpenAI, Google Vertex AI or similar) behind AI gateways, with authentication, rate limiting and resilience. Kubernetes experience, including GPU scheduling and auto-scaling. Infrastructure as code with Terraform (or equivalent); CI/CD for infrastructure. Strong Python experience to turn manual work into automated solutions. Observability experience with tools such as Splunk, Dynatrace, Datadog, Grafana or OpenTelemetry.
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations.
- Deep knowledge of one specific infrastructure technology and scripting languages
- Deep knowledge of cloud infrastructure and multiple cloud technologies with the ability to operate in and migrate across public and private clouds
Benefits & conditions
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
About the company
Chase is a leading financial services firm, helping nearly half of Americaβs households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
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