Sr Engineer, Software [T500-27090]

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 India Private Limited, operating as TMUS Global Solutions, has engaged ANSR, Inc. ("ANSR") as its exclusive recruiting partner. That means that any communications regarding TMUS Global Solutions opportunities or employment offers will be issued only through ANSR and the 1Recruit platform. If you receive a communication or offer from another individual or entity, please notify TMUS Global Solutions immediately. TMUS Global Solutions will never seek any payment or other compensation during the hiring process or request sensitive personal data (such as bank details or government-issued identification numbers) prior to a candidate’s acceptance of a formal offer.

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: As a Senior Engineer – Software, you will design, develop, and maintain scalable APIs, microservices, and integrations that support T-Mobile’s customer and operational platforms. You will focus on backend engineering using Java/Spring Boot, database performance optimization, Kubernetes-based deployments, and the modernization of legacy applications into cloud-native architectures. You will deliver high-quality, testable, and maintainable code; automate deployments; ensure system reliability; and contribute to technical stewardship through test automation, refactoring, and active management of technical debt. You will also apply AI coding tools, prompt engineering, and agentic patterns as a core part of your day-to-day SDLC — going beyond prototypes to production-grade use. 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:

• Design and develop Spring Boot REST APIs and GraphQL services with a focus on scalability, performance, and security.
• Implement microservices and API integrations supporting customer management, rating/charging, and operational processes.
• Refactor legacy applications into microservices using modern frameworks and patterns.
• Ensure code adheres to established engineering principles (SOLID, DRY, KISS, design patterns).
• Evaluate, design, and implement solutions using SQL/NoSQL services (Oracle, AWS RDS, Redis, Elasticsearch, DynamoDB, S3); optimize queries, indexes, and data models for high-performance workloads.
• Partner with data engineering teams to align database design with application performance and scalability goals.
• Deploy and manage applications on Kubernetes, with migration paths to cloud-native platforms (AWS, Azure, or GCP).
• Implement and maintain automated CI/CD pipelines, ensuring reliable builds and deployments.
• Integrate logging, monitoring, and alerting solutions to support production operations.
• Troubleshoot production issues across applications, databases, and distributed systems; conduct root cause analysis and implement corrective actions to prevent recurrence.
• Apply test-driven development (TDD) and maintain automated unit, integration, and regression test suites; ensure high code coverage in critical services.
• Track and remediate technical debt through systematic refactoring and modernization.
• Apply AI coding tools, prompt engineering, and agentic patterns as a core part of the SDLC — in production-grade workflows beyond prototypes (e.g., code generation, test generation, refactoring assistants, automated reviews, and agentic task execution within engineering pipelines).
• Conduct peer code reviews, provide actionable feedback, and mentor junior engineers in design, coding, testing, and deployment practices.
• Collaborate with cross-functional teams to integrate services with enterprise systems and batch pipelines; contribute to process improvements and adoption of emerging technologies.

What You’ll Bring: Required:

• 4+ years building and operating production-grade, customer-facing backend systems — not just prototypes or internal tools.
• Advanced proficiency in Java and Spring Boot, with hands-on REST and GraphQL API development you’ve shipped to production.
• Strong command of data structures, algorithms, and system design, including the ability to reason about complexity (Big O) and make sound trade-offs.
• Practical fluency with SQL and NoSQL data stores (Oracle, AWS RDS, Redis, Elasticsearch, DynamoDB, S3) — you design schemas and tune queries, not just consume them.
• Hands-on experience with Docker, Kubernetes, and cloud deployments (AWS, Azure, or GCP).
• Working experience with CI/CD pipelines, infrastructure-as-code, and DevOps workflows.
• Demonstrated use of AI coding tools, prompt engineering, and agentic patterns in real SDLC workflows — applied to production work, not just experiments.
• Proven ability to troubleshoot complex production issues across distributed systems and drive root-cause fixes.
• Track record of performing code reviews, mentoring peers, and holding the line on engineering standards.
• Bachelor’s degree in computer science, Engineering, or a related field — or equivalent demonstrated experience.

Nice to Have:

• Experience modernizing legacy monoliths into cloud-native microservices.
• Familiarity with API security, API gateways, and frontend integration patterns.
• Exposure to observability tooling (logging, metrics, tracing) and production on call.
• Practical knowledge of functional programming concepts alongside OOP.

Must Have Skills:

• Java and Spring Boot.
• REST and GraphQL API development.
• SQL and NoSQL data stores (Oracle, Redis, Elasticsearch, AWS RDS, DynamoDB, S3).
• Docker and Kubernetes.
• CI/CD pipelines and DevOps workflows.
• Test-driven development with automated unit, integration, and regression coverage.
• Applied AI coding tools, prompt engineering, and agentic patterns in the SDLC (production-grade, beyond prototypes).