Sr AI Engineer

Build production-ready agentic AI for customer service at T-Mobile in Frisco, TX (onsite), where you will design, optimize, and deploy Generative AI and LLM workflows that connect to enterprise systems. This senior role pairs advanced engineering with a focus on measurable reliability, security, and observability, supported by a comprehensive benefits package.

Responsibilities

• Design, develop, and deploy scalable, production-grade Generative AI applications, LLM-powered solutions, and agentic AI systems to support enterprise operations and customer service automation.
• Architect and implement AI agents and multi-agent orchestration workflows using modern frameworks such as LangGraph, LangChain, or equivalent technologies.
• Develop Retrieval-Augmented Generation (RAG) solutions using embeddings, vector databases, semantic search, and enterprise knowledge sources.
• Build and integrate RESTful APIs, Model Context Protocol (MCP) connectors, and enterprise data services to enable secure AI interactions with internal and external systems.
• Improve AI performance through prompt engineering, model selection, retrieval optimization, fine-tuning, and efficient inference strategies to enhance automation outcomes.
• Create AI evaluation frameworks to measure accuracy, hallucination rates, reliability, latency, throughput, and cost efficiency aligned to customer satisfaction goals and strategic objectives.
• Develop cloud-native AI solutions on Azure, AWS, or equivalent platforms, including containerization, automated deployment, and scalable architectures.
• Implement security, governance, and responsible AI practices such as authentication, authorization, data privacy, prompt injection protection, and enterprise compliance requirements.
• Set up observability for AI applications and agentic workflows, including logging, monitoring, and production troubleshooting capabilities.
• Partner with cross-functional teams across engineering, architecture, product, cybersecurity, and business to integrate AI-driven enhancements into production.
• Conduct technical and code reviews, mentor engineers, and help define reusable engineering standards and best practices.
• Research emerging AI technologies and open-source frameworks to support innovation and continuous improvement for customer service use cases.
• Perform other duties and projects as assigned by business management.

Requirements

• 5+ years of related experience and a Bachelor’s Degree (or advanced degree with 3 years of related work experience).
• Strong proficiency in Python, software engineering principles, and object-oriented programming.
• Experience designing, developing, securing, and integrating RESTful APIs using FastAPI or equivalent.
• Hands-on experience building with LLMs, including prompt engineering, structured outputs, function calling, and tool integration.
• Experience with agentic AI and orchestration using LangGraph, LangChain, or similar frameworks.
• Knowledge of embeddings, vector databases, semantic retrieval, document processing, and data integration.
• Experience developing and deploying applications on Azure, AWS, or Google Cloud.
• Proficiency with Git, CI/CD pipelines, automated testing, and production software development practices.
• Ability to design scalable, secure, reliable, and maintainable distributed systems.
• Strong analytical skills working with structured and unstructured data.
• Understanding of AI evaluation, performance benchmarking, accuracy measurement, and AI quality assurance.
• Strong communication, problem-solving, and cross-functional collaboration skills.
• At least 18 years of age and legally authorized to work in the United States.

Technologies

Python, RESTful APIs, FastAPI, LLMs, LangGraph, LangChain, Model Context Protocol (MCP), RAG, embeddings, vector databases, semantic search, Azure, AWS, Google Cloud, containerization, CI/CD pipelines, Git, authentication, authorization, prompt injection protection

Preferred

• Experience with Model Context Protocol (MCP) and enterprise AI tool integrations.
• Experience with Docker, Kubernetes, and cloud-native deployment tooling for AI workloads.
• Certified Analytics Professional (CAP).
• NVIDIA Deep Learning AI Certification.

Certifications

• Preferred: Certified Analytics Professional (CAP).
• Preferred: NVIDIA Deep Learning AI Certification.
• Preferred: Certified Data Scientist (CDS).

Compensation

National Base Pay Range: USD 133,100 - 240,100 per year
Total Target Cash Earnings Opportunity: $153,065 - $276,115

Benefits

• Medical, dental and vision insurance
• Flexible spending account
• 401(k)
• Employee stock grants
• Employee stock purchase plan
• Paid time off and up to 12 paid holidays
• Paid parental and family leave
• Family building benefits
• Back-up care
• Enhanced family support
• Childcare subsidy
• Tuition assistance
• College coaching
• Short- and long-term disability
• Voluntary AD&D coverage
• Voluntary accident coverage
• Voluntary life insurance
• Voluntary disability insurance
• Voluntary long-term care insurance
• Mobile service & home internet discounts (eligible employees)
• Pet insurance (eligible employees)
• Access to commuter and transit programs (eligible employees)
• Annual bonus or periodic sales incentive or bonus (eligible regular, non-temporary roles)
• Year-end bonus for corporate employees (eligible)