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You will need to reside within 50 miles of our Corporate Headquarters in Scottsdale, AZ as this role has the option of hybrid or onsite. Job Summary Artificial Intelligence is transforming the way businesses work, and Consumer Cellular's Data & AI organization is looking for an AI Engineer who wants to help build that future.
As an
AI Engineer, you'll partner with business leaders, engineers, and data professionals to build AI-powered applications, machine learning models, and decision-support tools that help our frontline teams deliver exceptional service to customers.
This role is ideal for someone with a strong foundation in AI, Machine Learning, Data Engineering and Science, or Computer Science who is excited to apply it in a real-world business setting. We value curiosity, creativity, and a willingness to learn as much as prior experience.
As part of the Data & AI organization, you'll work with data engineers, data scientists, and platform teams on our Databricks and AWS ecosystem, with exposure to technology leadership, and help shape how AI is used across Consumer Cellular.
Key Responsibilities AI Solution Development - Design, build, test, and deploy AI-powered applications and intelligent automation.
- Develop machine learning models that improve business operations and customer experiences.
- Build AI assistants and decision-support tools that help frontline employees serve customers.
- Develop RAG and LLM-based solutions using enterprise knowledge, applying prompt engineering and model optimization.
- Build AI agents and multi-step workflows that integrate with enterprise systems, data, and tools.
Business Partnership - Partner with business stakeholders to understand operational challenges and identify where AI can help.
- Lead discovery sessions with business teams to gather requirements.
- Prototype AI solutions for teams across the company.
- Translate technical concepts into plain language for business users.
Software Engineering - Write clean, maintainable, and scalable code, following engineering best practices and code reviews.
- Build APIs and integrations that support AI applications.
- Collaborate with agile teams to deliver high-quality solutions.
- Troubleshoot and resolve issues in AI-powered applications.
Data Engineering & Platform
- Partner with Data Engineering on the pipelines, feature stores, and vector indexes that power AI applications.
- Ensure data quality, lineage, and accessibility for model training and RAG in Databricks.
Responsible AI & Governance
- Apply Responsible AI principles (fairness, transparency, explainability, and human oversight) across the AI lifecycle.
- Protect customer and employee data in line with privacy, security, and regulatory requirements, including PII and CPNI.
- Document models, data sources, and design decisions per enterprise AI governance policies.
Learning & Innovation
- Stay current on advances in AI, machine learning, LLMs, generative AI, and AI agents, and share ideas with the team.
- Continuously build skills through experimentation and professional development.
Collaboration
- Work closely with software engineers, product managers, data engineers, and business leaders.
- Contribute ideas that reimagine business processes and improve employee and customer experiences.
- Support the rollout of enterprise AI initiatives.
