Sr Engineer, Site Reliability [T500-20463]

ANSR is hiring for one of its clients.

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.

About 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.

TMUS India Private Limited is a subsidiary of T-Mobile US, Inc. and operates as TMUS Global Solutions.

About the Role :

The Senior Site Reliability Engineer (Performance) is a hands-on engineering role focused on ensuring that customer-facing and internal applications deliver optimal performance, scalability, and resiliency. This role goes beyond traditional testing—profiling Java / Spring Boot applications, tuning Kubernetes workloads, analyzing network issues, and applying cloud-native best practices to drive systemic improvements. The engineer designs and automates performance tests, formulates hypotheses, and uses data-driven insights to recommend or implement fixes at code, infrastructure, and architecture levels. With an automation-first mindset, they embed performance engineering into CI / CD pipelines and partner with developers, architects, and SREs to create a performance-first culture.

What You’ll Do :

• Profile and optimize Java / Spring Boot microservices, diagnosing memory leaks, GC issues, thread contention, and improving latency and throughput
• Design and execute performance tests (load, stress, spike, endurance) using tools such as JMeter, k6, Gatling, Locust, or LoadRunner
• Develop reusable test frameworks and integrate performance tests into CI / CD pipelines
• Build load / capacity models and design experiments to test scalability under real-world conditions
• Analyze and optimize Kubernetes workloads (EKS / AKS / GKE), tuning autoscaling, pod configs, and Helm charts
• Use observability tools (AppDynamics, Prometheus, Grafana, Splunk) and tracing to identify performance bottlenecks
• Conduct performance diagnostics across network layers (TCP / IP, gRPC, HTTP / REST)
• Mentor engineers and participate in design reviews to embed performance practices from the start

What You’ll Bring :

Must Have Skills :

Nice To Have :