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About This Role
Senior AI Engineer (260531\)Our Commitment to You
At Consumer Cellular, recruiting is human. Every application is reviewed by a real member of our Talent Acquisition team because we believe the people behind the résumé matter just as much as what's on it.
All official communication from Consumer Cellular will come from a @consumercellular.com email address or through our verified texting platform, which will only be used to schedule interviews. We will never ask for personal and financial information during the recruiting process. If you receive outreach that doesn't match these criteria, please do not engage and feel free to verify directly at talentacquisition@consumercellular.com.
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
Consumer Cellular is seeking a visionary Senior AI Engineer to lead the design, strategy, and execution of Artificial Intelligence solutions that transform how we serve customers and empower employees.
Reporting directly to the Chief Information Officer, this highly visible role will define the company's AI roadmap while partnering with executive leadership and business domain owners to identify opportunities where AI can fundamentally improve business outcomes.
This leader will combine deep technical expertise with strategic business acumen to design intelligent systems, machine learning solutions, and AI\-powered decisioning agents that improve employee productivity, elevate customer experiences, and reimagine work across the enterprise.
Success in this role requires someone who is equally comfortable discussing enterprise AI strategy with executives, facilitating innovation workshops with business leaders, and designing scalable AI architectures that move from concept to production.
This is more than an engineering role—it's an opportunity to shape the future of work at Consumer Cellular.
What You Will Do
AI Strategy \& Enterprise Transformation
- Develop and execute Consumer Cellular's enterprise AI strategy aligned with business priorities.
- Identify opportunities where Artificial Intelligence can fundamentally improve operations, customer experiences, and employee productivity.
- Partner with executive leadership and business stakeholders to create AI roadmaps and implementation strategies.
- Lead AI discovery sessions across Customer Care, Retail, Sales, Marketing, Finance, HR, Operations, and Technology.
- Challenge existing business processes by reimagining how work should be performed in an AI\-enabled organization.
- Prioritize AI initiatives based on business value, feasibility, customer impact, and operational efficiency.
- Build executive\-level business cases demonstrating measurable ROI for AI investments.
AI Solution Architecture
- Design enterprise\-scale AI solutions supporting customer\-facing and employee\-facing experiences.
- Architect intelligent decisioning agents that augment frontline employees during customer interactions.
- Design Retrieval\-Augmented Generation (RAG) architectures leveraging enterprise knowledge.
- Build scalable AI platforms capable of supporting multiple business domains.
- Define standards for AI architecture, model governance, observability, security, and responsible AI.
- Evaluate emerging AI technologies and determine applicability within Consumer Cellular.
Machine Learning \& AI Engineering
- Design, develop, deploy, and optimize production\-ready machine learning solutions.
- Build predictive and prescriptive models supporting customer retention, sales optimization, workforce management, fraud detection, and operational efficiency.
- Develop AI copilots and intelligent assistants using Large Language Models.
- Optimize prompts, model performance, reasoning quality, and AI workflows.
- Establish MLOps standards supporting enterprise deployment and lifecycle management.
Intelligent Agent Development
Lead Development of AI Agents capable of
- Customer service decision support
- Knowledge retrieval
- Workflow orchestration
- Next\-best\-action recommendations
- Employee coaching
- Quality assurance automation
- Contact summarization
- Customer journey optimization
These agents should improve employee decision making while preserving the human connection that defines Consumer Cellular's customer experience.
Business Partnership
- Build trusted relationships with executive leaders and business domain experts.
- Translate operational challenges into AI\-enabled business solutions.
- Lead AI workshops focused on innovation and future\-state process design.
- Influence business leaders to adopt AI\-driven operating models.
- Communicate complex AI concepts to technical and non\-technical audiences.
Technical Leadership
- Provide technical leadership for enterprise AI initiatives.
- Mentor engineers and promote AI best practices.
- Establish coding standards, architecture patterns, and engineering excellence.
- Drive experimentation while maintaining production\-quality engineering discipline.
- Stay ahead of emerging technologies including:
+ Large Language Models
+ Agentic AI
+ Autonomous AI Systems
+ Machine Learning
+ Multi\-Agent Frameworks
+ AI Governance
+ Intelligent Automation
Minimum Qualifications
- Bachelor’s degree in related field or equivalent experience
- Master's degree preferred
- 8\+ years of software engineering experience.
- 5\+ years designing and deploying enterprise AI or Machine Learning solutions.
- Experience building production AI applications used by thousands of users.
- Experience creating enterprise AI strategies and technology roadmaps.
- Experience partnering directly with executive leadership and business stakeholders.
- Experience leading cross\-functional technology initiatives.
- Experience designing AI platforms from concept through enterprise implementation.
- Demonstrated success delivering measurable business outcomes through AI.
Technical Expertise
Artificial Intelligence
- Large Language Models (OpenAI, Anthropic, Gemini, Llama)
- Prompt Engineering
- Retrieval\-Augmented Generation (RAG)
- Agentic AI
- Multi\-Agent Systems
- AI Orchestration
- Semantic Search
- Embeddings
- Vector Databases
- AI Evaluation Frameworks
Machine Learning
- TensorFlow
- PyTorch
- Scikit\-Learn
- NLP
- Deep Learning
- Reinforcement Learning (preferred)
- Predictive Analytics
Programming
- Python
- SQL
- REST APIs
- C\#
- JavaScript
Cloud Platforms (Experience with one or more)
- Microsoft Azure AI
- Azure OpenAI
- Azure Machine Learning
- AWS AI Services
- Google Vertex AI
MLOps
- Git
- CI/CD
- Docker
- Kubernetes
- LMflow
- Model Monitoring
- AI Observability
- Model Governance
Leadership Competencies
- Strategic thinking
- Executive presence
- Innovation mindset
- Business consulting skills
- Systems thinking
- Strong influence without authority
- Excellent communication
- Ability to simplify complex technical concepts
- Curiosity and continuous learning
- Customer\-first decision making
Preferred Qualifications
- Experience implementing AI within customer service or contact center environments.
- Telecommunications industry experience.
- Experience building AI copilots for frontline employees.
- Experience implementing Microsoft Copilot or enterprise copilots.
- Experience with enterprise knowledge management platforms.
- Experience developing AI governance frameworks.
- Experience with quality assurance automation.
- Experience leading AI Centers of Excellence.
About Consumer Cellular
Founded in 1995, Consumer Cellular is the first wireless provider unapologetically built for Americans 50\+. An approved wireless partner of AARP, Consumer Cellular is trusted by more than 4 million subscribers for affordable plans, popular phones and devices, and great nationwide coverage, all backed by top\-rated, 100% U.S. based customer support. Based in Scottsdale, AZ, with 3,000 employees in company locations throughout the U.S., Consumer Cellular has earned recognition as the most awarded wireless brand for customer service. The company has been honored as \#1 in customer service in its industry numerous times and, in 2024, ranked \#1 in network coverage and customer satisfaction among wireless carriers by American Customer Satisfaction Index (ACSI). Additionally, the company has been featured 12 times on the Inc. 5000 list of the fastest\-growing privately held U.S. companies. Consumer Cellular phones, devices and plans are available nationwide through our company\-owned neighborhood stores, online at ConsumerCellular.com, by phone at (888\) 345\-5509, and at leading retailers including Walmart. Connect with Consumer Cellular on Facebook, Instagram, and Youtube for tutorials, features, applications, and company news.
Pay \& Benefits Data (in accordance with the Equal Pay and Opportunities Act)
- Minimum Salary: $138,600
- Maximum Salary: $200,550
This information reflects the anticipated base salary range for this position based on current national data. Minimums and maximums may vary based on location. Individual pay is based on skills, experience and other relevant factors. Our Talent Acquisition team are able to answer any additional questions you may have as you move through the selection process. As part of our Total Rewards package, Consumer Cellular, Inc. offers a broad range of Health, Life, Voluntary Lifestyle and other benefits and perks that enhance your physical, mental, and emotional wellbeing.
- Competitive base pay with potential for shift differential, overtime and bonus pay
- Medical insurance (98% company\-paid for full\-time employee only coverage)
- Dental and Vision insurance (100% company\-paid for full\-time employee only coverage)
- 401(k) company match of 100% up to 6% of your pay
- Discounted Consumer Cellular wireless phone plan for employees
- Paid Time Off (PTO) available following a 30\-day waiting period\*
- 6 company\-paid holidays plus 16 hours of floating holiday accrual per year
- Flexible Spending Accounts (FSA) for health care and dependent care expenses
- Life and AD\&D insurance equal to 1x your annual earnings (100% company\-paid)
- Long\-Term Disability insurance (100% company\-paid)
- Employee Assistance Program (100% company\-paid)
- Education reimbursement
- Employee rewards program
- *Accrue up to 40 hours in 1st year for hourly positions and up to 120 hours for salaried positions.*
Primary Location: United States\-Arizona\-Scottsdale 9363 E Bahia Dr 9363 E Bahia Dr Scottsdale 85260
Job: Information Technology
Schedule: Full\-time
Travel: No
Job Posting: Jul 13, 2026
Unposting Date: Jul 19, 2026
Salary Context
This $138K-$200K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Consumer Cellular, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($169K) sits 22% below the category median. Disclosed range: $138K to $200K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Consumer Cellular AI Hiring
Consumer Cellular has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in Scottsdale, AZ, US. Compensation range: $161K - $367K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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