Platform Engineer - AI Observability & Governance (OpenShift)

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.

Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.

We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.

Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Job Description:

This role engineers and operates enterprise vendor platforms in our on-premises Red Hat OpenShift environment. You will own the deployment, configuration, reliability, and day-to-day support of a self-hosted AI observability platform that provides tracing, monitoring, and evaluation for GenAI applications across the bank. The platform runs as a set of containerized services backed by stateful data stores, so experience operating databases and storage on OpenShift or Kubernetes is central to the role.

This is a platform and systems engineering role, not a model development role. The focus is keeping a business-critical, third-party platform secure, stable, performant, and compliant as trace volumes and adoption grow. You will work closely with the vendor, OpenShift platform teams, information security, data governance, and the application teams that consume the service.

Exposure to AI tooling is helpful, but what matters most is a track record of running enterprise platforms in production. The ideal engineer is hands-on, comfortable owning production issues end to end, picks up new tools quickly, and can lead cross-functional work to get things done.

Responsibilities

• Deploy, configure, upgrade, and support vendor applications on on-premises OpenShift using Helm and CI/CD pipelines.

• Manage OpenShift namespaces, resource quotas, storage classes, networking, routes, and network policies.

• Deploy and operate stateful backing services (e.g., PostgreSQL, Redis, ClickHouse, object storage), including persistent storage, replication, backup and restore, and encryption at rest.

• Plan capacity and manage data retention and storage growth for high-volume trace and telemetry data.

• Onboard vendor container images and Helm charts into internal registries and drive remediation of image vulnerability findings.

• Build and maintain infrastructure and application monitoring, logging, and alerting (e.g., Splunk, Dynatrace, Prometheus, Grafana).

• Lead production incident response, root cause analysis, and permanent fixes; manage vendor escalations through resolution.

• Implement and maintain security controls, including TLS certificates, secrets management, SSO/OAuth integration, and access management workflows.

• Support governance and control requirements, including audit logging, data documentation, access reviews, and evidence for technology risk reviews.

• Design, document, and test high availability, backup, and disaster recovery/contingency procedures.

• Automate environment builds, deployments, and code promotion across development, test, and production; create and maintain runbooks.

• Support application teams onboarding to the platform and troubleshoot integration issues (APIs, authentication, connectivity).

• Mentor engineers and drive engineering standards across internal, offshore, and vendor teams.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, MIS, related field, or equivalent experience.

• 10+ years of software, systems, or platform engineering experience supporting production applications.

• Hands-on experience deploying and operating workloads on Red Hat OpenShift or Kubernetes in production.

• Experience running stateful services on OpenShift or Kubernetes, such as PostgreSQL, Redis, or analytical databases, including storage, backup, and recovery.

• Experience supporting third-party/vendor enterprise platforms end to end, including installs, upgrades, patching, and vendor escalations.

• Strong Linux (RHEL) administration and troubleshooting skills.

• Experience with Helm, container registries, and CI/CD pipelines.

• Scripting and automation experience with Python, Bash, or similar.

• Experience with infrastructure and application observability tools such as Splunk, Dynatrace, Prometheus, or Grafana.

• Working knowledge of enterprise security controls, including TLS certificates and trust stores, secrets management, encryption, SSO/OAuth, and role-based access.

• Experience working in Agile environments.

• Demonstrated technical leadership and stakeholder influence.

Desired Qualifications

• Experience delivering technology solutions in large, complex, regulated organizations, preferably financial services.

• Experience operating ClickHouse or other high-volume analytical/time-series data stores.

• Experience supporting technology risk, audit, or data governance requirements for production platforms.

• Experience supporting platforms used by GenAI/LLM applications, or familiarity with LLM tracing, evaluation, or AI observability tools.

• Familiarity with LLM application frameworks (e.g., LangChain) or OpenAI-compatible APIs.

• Experience with configuration management or infrastructure-as-code tooling.

• Strong collaboration skills and ability to quickly learn emerging technologies.

Skills:

• Application Development
• Automation
• Influence
• Solution Design
• Technical Strategy Development
• Architecture
• Business Acumen
• DevOps Practices
• Result Orientation
• Solution Delivery Process
• Analytical Thinking
• Collaboration
• Data Management
• Risk Management
• Test Engineering

Shift:

Hours Per Week: