Senior Manager (DevOps, Automation, GCP)

CVS Health•Work At Home-Connecticut, MA

2d•$106,605 - $260,590

About The Position

Join Fortune 7 CVS Health as a Sr. Manager, Software Engineering - DevOps, Observability & Monitoring to lead strategic initiatives for the CVS Caremark Digital team. In this role, you will drive the vision and execution of modern platform engineering capabilities that enable scalable, reliable, and secure application development. You will build and lead a high-performing engineering team responsible for designing, implementing, and operating cloud-native platforms. The ideal candidate is a hands-on leader with deep technical expertise in cloud architectures, DevOps, and observability, combined with the ability to lead transformation and operational excellence initiatives.

Requirements

5+ years of experience in software engineering, SRE, or production engineering within large-scale distributed systems.
Hands-on experience with AIOps or intelligent monitoring platforms, including anomaly detection and event correlation.
Experience with observability tools such as AppDynamics, Grafana, Prometheus, and Splunk.
Strong expertise in cloud platforms (AWS, Azure, or GCP), cloud-native architectures (Kubernetes, containers, microservices), and CI/CD pipelines (GitHub Actions, Jenkins).
Experience with Infrastructure as Code (Terraform, AWS CloudFormation, or GCP Deployment Manager).
Proficiency in at least one programming language (e.g., Python, Java, Go).
Proven track record of improving operational metrics (SLAs, CSAT, resolution time).
Experience with GenAI and automation tools such as OpenAI, Copilot, Gemini, Claude, and MCP.
Strong understanding of distributed systems, resiliency patterns, and fault tolerance.
Strong analytical skills with experience in reporting and performance measurement.
Excellent communication, stakeholder management, and conflict resolution skills.
Ability to thrive in a fast-paced, high-growth, or matrixed environment.
Bachelor’s degree (or equivalent experience) in Computer Science, Engineering, or a related discipline.
Customer-first mindset with a passion for delivering exceptional service.
Strategic thinker with strong execution capabilities.
High emotional intelligence with strong people leadership skills.
Continuous improvement mindset with a focus on innovation.

Nice To Haves

Experience designing and implementing AIOps platforms or predictive reliability systems at scale.
Strong knowledge of machine learning applications in IT operations (e.g., anomaly detection, forecasting, clustering).
Experience defining and managing SLIs/SLOs and error budgets at scale.
Experience with OpenTelemetry and modern observability standards.
Familiarity with chaos engineering, resilience testing, and fault injection frameworks.
Exposure to GenAI-driven operations or AI-assisted troubleshooting tools.
Experience in healthcare, financial services, enterprise SaaS, or other regulated industries.
Proven ability to lead cross-functional initiatives and influence senior stakeholders.
Contributions to open-source projects related to SRE, observability, or AIOps.
Relevant certifications in cloud platforms, SRE, AIOps, OpenTelemetry, or DevOps are a plus.

Responsibilities

Lead, mentor, and grow a team of software engineers and SRE/DevOps engineers.
Foster a culture of accountability, innovation, and continuous improvement.
Define team goals, OKRs, and performance metrics aligned with organizational strategy.
Partner with product, architecture, and business stakeholders to deliver platform capabilities.
Drive the adoption of AIOps solutions for predictive monitoring, anomaly detection, and automated root cause analysis.
Integrate machine learning models and analytics into monitoring pipelines to proactively detect and prevent incidents.
Develop intelligent alerting systems to reduce noise and improve signal quality.
Architect and implement scalable observability frameworks across metrics, logs, traces, and events.
Establish standards for instrumentation, telemetry collection, and distributed tracing.
Enable proactive monitoring, alerting, and incident detection using tools such as Datadog, Prometheus, Grafana, and Splunk.
Define and implement enterprise-wide SRE practices, including SLIs, SLOs, error budgets, and reliability governance.
Drive adoption of CI/CD pipelines, Infrastructure as Code (IaC), and GitOps practices.
Lead the design and evolution of scalable, automated, and secure platform engineering solutions.
Standardize development and deployment workflows across teams.
Champion DevOps maturity, developer productivity, and release automation.
Improve system reliability through error budgets, resiliency patterns, and chaos engineering.
Lead incident response processes, postmortems, and root cause analysis.
Drive continuous improvements in MTTR (Mean Time to Recovery) and system availability.
Architect and manage solutions across cloud platforms (AWS, Azure, or GCP).
Ensure scalability, security, and cost optimization of infrastructure.
Oversee containerization and orchestration using Docker and Kubernetes.
Integrate DevSecOps practices into pipelines and platform tooling.
Ensure compliance with enterprise security standards and regulatory requirements.
Automate security scanning, vulnerability management, and policy enforcement.