Sr Engineer, Site Reliability [T500-27069]

About T-Mobile: T-Mobile US, Inc. (NASDAQ: TMUS), headquartered in Bellevue, Washington, is America’s supercharged Un-carrier, connecting millions through its strong nationwide network and flagship brands, T-Mobile and Metro by T-Mobile. Customers benefit from an unmatched combination of value, quality, and exceptional service experience.

TMUS Global Solutions: TMUS Global Solutions is a world-class technology powerhouse accelerating the company’s global digital transformation. With a culture built on growth, inclusivity, and global collaboration, the teams here drive innovation at scale, powered by bold thinking.

About the Role: Tax Technology Solutions operates business-critical tax platforms across multi-cloud and on-prem environments, integrating with billing, ERP, and financial systems. System availability, accuracy, and compliance directly impact enterprise operations. We pride ourselves on encouraging a culture of innovation, agile ways of working, and transparency in all we do. Join us in embodying the spirit of the Un-carrier and make a tangible impact!

What You’ll Do:

• The Senior Engineer, Systems Reliability is responsible for defining and advancing the reliability, resilience, and operational maturity of T-Mobile's Tax Technology platforms.
• Define and govern SLOs, SLIs, and reliability standards across tax systems.
• Design resilience strategies (failover models, scaling patterns, high availability architecture).
• Provide reliability-focused design input into application and cloud architecture decisions to ensure long-term system resilience.
• Define observability strategy, standards, and SLO-aligned monitoring frameworks to support reliability objectives.
• Identify and proactively mitigate system reliability risks across cloud and hybrid architectures, including failure modes, scaling behavior, and resilience patterns.
• Define and drive reliability automation strategy, identifying opportunities to reduce systemic risk and operational toil across platforms.
• Lead major incident command efforts and establish post-incident remediation standards.
• Own compliance governance for production systems and partner with audit teams to ensure regulatory readiness.
• Oversee vulnerability management prioritization and long-term remediation strategy.

What You’ll Bring:

• 7+ years of experience in SRE or reliability engineering.
• Experience with Linux/Unix systems and automation/scripting.
• Experience designing reliability patterns in cloud-native environments leveraging containerization and orchestration platforms.
• Proven experience improving system availability and performance using observability tools and performance tuning techniques.
• Strong incident leadership experience.
• Experience in compliance-heavy or regulated environments preferred.
• Ability to influence engineering and architecture decisions without direct authority.
• Experience using AI-assisted tooling for incident analysis, log insights, and reliability optimization.

Must Have Skills:

• Experience designing reliability patterns in cloud-native and hybrid systems.
• Strong experience with cloud platforms (AWS preferred).
• Hands-on experience with containerization and orchestration (Docker, Kubernetes).
• Experience building and operating CI/CD pipelines (GitLab or equivalent).
• Experience implementing observability and monitoring solutions (metrics, logging, tracing).
• Experience leveraging AI/ML-powered tools for incident analysis, anomaly detection, and improving system reliability (AIOps).

Nice-to-Have:

• Experience with observability tools such as Splunk, Grafana, or OpenTelemetry.
• Experience with progressive delivery strategies (Blue/Green, Canary deployments).
• Experience with auto-scaling and performance optimization in cloud environments.
• Familiarity with relational databases (PostgreSQL, SQL Server, RDS).
• Understanding of secure system design (TLS, JWT, secrets management).
• Experience integrating AI/ML into observability or operations platforms (e.g., AIOps, anomaly detection, predictive alerting).
• Familiarity with LLM-based tools for code generation, runbook automation, or incident triage.
• Exposure to AI-driven automation frameworks or copilots in engineering workflows.
• Experience supporting regulated enterprise systems such as indirect tax engines or ERP-integrated platforms (Vertex O-Series a plus).
• Experience in compliance-driven environments and control frameworks.