AI Engineer

T-Mobile • Bachelor's Degree • Java • Python • SQL • 13 days ago

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Location

In office (Hyderabad)

Seniority

Middle · 4+ years exp

Overview

Company

Impact

Profile match

T-Mobile

T-Mobile US is a major American telecommunications carrier headquartered in Bellevue, Washington, operating as a publicly traded subsidiary majority-owned by Deutsche Telekom. The company provides nationwide wireless voice, data, and 5G mobile services alongside fixed wireless home internet to over 140 million subscribers. Known for its consumer-centric "Un-carrier" strategy, T-Mobile delivers connectivity through its flagship brand as well as prepaid subsidiaries like Metro by T-Mobile and Mint Mobile.

t-mobile.com • Hyderabad • Warsaw • Est. 2001

Requirements:

4 - 6 years of software engineering experience building distributed systems and cloud-native applications.
Strong proficiency in Python or Java, with working knowledge of both preferred.
Experience designing APIs, microservices, workflow engines, or platform services.
Experience building systems that integrate with LLMs, AI services, or conversational platforms.
Experience designing highly available distributed systems and service-oriented architectures.
Strong understanding of software architecture, system design, scalability, resiliency, and performance optimisation.
Demonstrated experience leading technical design discussions, driving architectural decisions, and influencing engineering direction across teams.
Experience with cloud-native technologies, including containers, Kubernetes, and service-based architectures.
Excellent problem-solving, debugging, and technical communication skills.
Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field, or equivalent practical experience.
Experience integrating AI systems with enterprise applications, APIs, tools, or data platforms through standardised integration patterns.

Must Have Skills:

Python software engineering.
Distributed systems, APIs, and microservices.
LLM, AI service, and conversational platform integration.
Cloud-native architecture, containers, and Kubernetes.
Software architecture and technical leadership.

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