Sr Software Engineer, Agentic AI at T-Mobile in Atlanta, GA

Sr Software Engineer, Agentic AI Location: Atlanta, Georgia At T-Mobile, we invest in YOU!  Our Total Rewards Package ensures that employees get the same big love we give our customers.  All team members receive a competitive base salary and compensation package - this is Total Rewards. Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches. That’s how we’re UNSTOPPABLE for our employees! Job Overview This role is responsible for designing, developing, and deploying scalable software and Agentic AI solutions that support intelligent customer engagement across mobile, web, and support platforms. The engineer will build AI-enabled applications, APIs, distributed services, and orchestration layers integrating LLMs, conversational AI, and enterprise systems into customer-facing and operational workflows. The role involves collaborating with engineering and platform teams to develop cloud-native microservices, distributed systems, and AI-driven workflows using modern technologies such as Kubernetes, virtualization, big data platforms, and AI orchestration frameworks. The engineer will contribute to systems supporting conversational and agentic AI capabilities across voice and text channels. This position requires strong technical judgment to resolve complex issues, contribute to software design decisions, and support highly available, scalable, and secure AI-enabled systems operating at scale. Success is measured by delivering reliable, extensible software solutions that improve operational efficiency and customer experience through intelligent AI-driven capabilities. Job Responsibilities: Design, develop, test, and deploy scalable software and Agentic AI solutions to support enterprise automation, intelligent workflows, and customer engagement platforms Build and enhance AI-enabled applications, backend services, APIs, and integration components using modern software engineering and cloud-native best practices Develop and implement multi-step AI workflows, orchestration logic, and agent-based systems leveraging LLMs, RAG architectures, and AI automation frameworks Contribute to the design of microservices and distributed systems supporting real-time voice and text-based customer interactions at scale Collaborate with cross-functional engineering, AI, platform, and product teams to deliver secure, reliable, and high-performing AI-driven solutions Evaluate emerging AI technologies, frameworks, and engineering practices to support innovation and align with business and technology strategy Implement AI reliability, monitoring, observability, security, and governance best practices, including guardrails and human-in-the-loop workflows Create and maintain technical documentation for software solutions, AI workflows, APIs, systemarchitecture, and operational processes Mentor team members through technical guidance, code reviews, knowledge sharing, and adoption of AI engineering best practices Support continuous improvement initiatives, operational excellence, and other engineering projects as assigned by business leadership Education and Work Experience: Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required) Acceptable areas of study include Computer Science, Software Engineering, Information Management or equivalent experience in field (Required) 4-7 yearsTechnicalengineering experience. (Required) Knowledge, Skills and Abilities: Strong communication, collaboration, and customer-focused problem-solving skills Stronganalytical, troubleshooting, and technical documentation abilities Experience developing scalable software applications and AI-enabled services using Python, Java, or C++ Experience with cloud-native distributed systems, APIs, microservices, and real-time integration platforms Familiarity with LLMs, conversational AI, agentic AI workflows, and AI orchestration frameworks Experience building AI-driven automation, RAG solutions, and enterprise AI integrations Understanding of scalability, reliability, observability, and secure software engineering best practices for production AI systems Preferred Qualifications: Experience designing and deploying cloud-native AI solutions using Docker, Kubernetes, and scalable microservices architectures Experience building and integrating AI-enabled applications, conversational AI platforms, agentic AI workflows, and enterprise automation systems Strong familiarity with Large Language Models (LLMs), prompt engineering, tool orchestration, and AI-assisted development workflows Experience supporting highly available, scalable, and production-grade distributed systems and AI platforms Experience developing or supporting voice and text-based customer engagement and conversational AI solutions Familiarity with AI orchestration frameworks, RAGarchitectures, and real-time AI integration patterns for enterprise applications At least 18 years of age Legally authorized to work in the United States Additional Locations: Seattle, Washington