Job Description
This Sr. AI Engineer leads the development, operationalization, and scaling of advanced AI systems and autonomous agents that transform enterprise productivity, and enable intelligent decision-making. This role drives the evolution of enterprise-grade AI platforms and solutions leveraging Large Language Models (LLMs), Agentic AI architectures, and Retrieval-Augmented Generation (RAG) frameworks to deliver measurable impact across business functions. As a senior technical contributor, this individual provides thought leadership in LLM engineering, multi-agent orchestration, and GenAI integration, ensuring alignment with T-Mobile’s broader innovation roadmap. The Senior Engineer partners with data scientists, and engineering teams to architect, deploy, and continuously refine intelligent systems that scale securely and responsibly across the enterprise.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Skills and Requirements
4-7 years of experience in AI/ML engineering, intelligent automation, or applied AI systems development in an enterprise environment
4-7 Years of experience in architecting and deploying sophisticated agentic AI systems to enhance reasoning and interaction capabilities in complex workflows
Hands-on experience with LLM development, OpenAI API usage, custom GPT creation, and RAG implementations. MCP/A2A/ACP familiarity, Agent Evals
Proficiency in Python with experience in libraries such as PyTorch, TensorFlow, LangChain, or similar.
Ability to analyze and interpret complex data to improve AI model responses.
LLM & Agentic Systems: Expert in prompt & context engineering, fine-tuning, and orchestrating multi-agent AI frameworks.
Strong proficiency in designing and optimizing retrieval-augmented generation pipelines using vector databases and semantic search.
Experience embedding AI into large-scale enterprise systems, with focus on scalability, compliance, and performance.
Bachelor's Degree plus 5 years of related work experience
OR advanced degree with 1 year of related work experience
OR combination of education and experience deemed equivalent - Proficiency in documenting AI system architectures, processes, and user guides.