Senior Level Observability Engineer Jobs
Senior level observability engineer jobs place experienced engineers in charge of monitoring strategy, platform reliability, and the technical direction of the teams that build and maintain it. Openings concentrate in Technology & Software, Insurance, and Manufacturing, with 100% remote or hybrid availability, and employers like CVS Health, Fanduel, and Ensono hiring at this level now.
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Showing 5 of 11+ Senior Level Observability Engineer jobs
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:
1st shift (United States of America)Hours Per Week:
40Job 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:
1st shift (United States of America)Hours Per Week:
40See All 11 Senior Level Observability Engineer Jobs
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Top Industries Hiring
- Technology & Software
- Insurance
- Manufacturing
- Electronics & Hardware
- Banking & Financial Services
Senior Level Observability Engineer Jobs: Frequently Asked Questions
How do I get a senior level observability engineer job?
Employers hiring at the senior level look for engineers who have owned observability platforms end to end, not just contributed to them. Demonstrating that you have set standards for metrics, logging, and tracing across a production environment carries more weight than tool familiarity alone. Strong candidates can also speak to how they have mentored teammates and influenced architectural decisions, not only executed them.
Which companies hire senior level observability engineers?
Companies hiring senior level observability engineers right now include CVS Health, Fanduel, and Ensono, based on current listings on Migrate Mate as of November 2026. At this level, hiring tends to come from organizations running complex distributed systems where observability is treated as a first-class engineering discipline, including large technology firms, financial services companies, and cloud-native product companies.
Are there remote senior level observability engineer jobs?
Yes, remote and hybrid availability is strong at the senior level. About 100% of senior level observability engineer openings are remote or hybrid as of November 2026, reflecting how many engineering organizations treat experienced observability hires as distributed contributors. On-site roles do exist, particularly at companies with strict infrastructure or compliance requirements.
What makes an observability engineer role senior level?
A senior level observability engineer role is defined by ownership and scope rather than task execution. Senior engineers are expected to set the observability strategy for a platform or organization, evaluate and select tooling, define SLO and alerting standards, and lead the work of more junior engineers. The role typically involves cross-functional collaboration with SRE, platform, and product teams rather than working within a single defined scope.
Which industries hire the most senior level observability engineers?
Senior level observability engineer roles concentrate in Technology & Software, Insurance, and Manufacturing, based on current listings on Migrate Mate as of November 2026. These sectors tend to operate high-availability, high-complexity systems where the cost of downtime or degraded performance is significant, making experienced observability engineers a consistent hiring priority.