📍 Job Overview

Job Title: Senior AI Platform Engineer II
Company: Axon
Location: Scottsdale, Arizona, United States
Job Type: Hybrid
Category: AI & Machine Learning Engineer
Date Posted: 2025-06-18
Experience Level: 2-5 years
Remote Status: Hybrid (Seattle, Scottsdale, San Francisco, Atlanta, Boston)

🚀 Role Summary

Collaborate with cross-functional teams to deploy and integrate GPT-driven applications across various platforms and services.
Support the creation of training materials and documentation to promote effective use of GPT and LLMs.
Assist in identifying potential design improvements to ensure scalability and efficiency of AI projects.
Keep up-to-date with the latest trends in AI, machine learning, and cloud services, bringing fresh ideas to the team.
Enable innovation and value creation by participating in brainstorming sessions to identify new ways to apply GPT technologies for business value.

📝 Enhancement Note: This role requires a strong background in software development and a passion for AI technologies, with a focus on GPT and LLM deployment. Familiarity with cloud platforms and programming languages is essential for success in this position.

💻 Primary Responsibilities

Assist in Deployment and Integration:
- Help implement patterns for deploying GPT-driven applications across various platforms and services.
- Collaborate with the team to build and maintain connectors that enhance GPT functionalities within existing systems.
- Participate in evaluating and testing new AI services, providing feedback on usability and performance.
Contribute to Training and Best Practices:
- Support the creation of training materials and documentation to promote effective use of GPT and LLMs.
- Learn and help teach prompt engineering fundamentals to development teams.
- Document lessons learned and share knowledge to improve team-wide AI practices.
Support Architectural Guidance:
- Work with Corporate AI Team and solution architects to understand architectural approaches for GPT projects.
- Assist in identifying potential design improvements to ensure scalability and efficiency.
Enable Innovation and Value Creation:
- Participate in brainstorming sessions to identify new ways to apply GPT technologies for business value.
- Keep up-to-date with the latest trends in AI, machine learning, and cloud services, bringing fresh ideas to the team.
Collaboration and Communication:
- Work closely with data engineering, solution architecture, and business units to support ongoing GPT initiatives.
- Communicate updates, roadblocks, and technical insights clearly to team members and stakeholders.
Secure Developer Enablement:
- Learn and help maintain secure procedures for managing GPT API keys, ensuring compliance with Axon’s security standards.
- Assist in setting up monitoring and auditing processes to track usage and detect anomalies.

🎓 Skills & Qualifications

Education:

Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience).

Experience:

2-4 years of software development experience (internships or relevant projects may be considered).

Required Skills:

Familiarity with programming languages such as Python, Java, JavaScript, React, or similar.
Some cloud platform experience (e.g., AWS, Azure, GCP) and interest in expanding these skills.
A passion for AI and machine learning technologies and an eagerness to learn GPT/LLM deployment.
Basic understanding of security best practices and willingness to learn more about securing AI platforms.
Strong communication skills with an ability to work collaboratively in a fast-paced environment.

Preferred Skills:

Exposure to OpenAI, Azure ML Studio, or similar AI services.
Familiarity with data platforms such as Snowflake or any data integration tools.
Enthusiasm for exploring emerging AI and machine learning trends and applying them to real-world use cases.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

A portfolio showcasing your software development projects, with a focus on AI and machine learning applications.
Examples of GPT or LLM integration projects, if available.
Demonstrations of your understanding of cloud platforms and security best practices.

Technical Documentation:

Code quality, commenting, and documentation standards for your software development projects.
Version control, deployment processes, and server configuration examples.
Testing methodologies, performance metrics, and optimization techniques for AI and machine learning projects.

📝 Enhancement Note: While a portfolio of AI and machine learning projects is not explicitly required, it is strongly recommended to demonstrate your skills and understanding of the technologies relevant to this role.

💵 Compensation & Benefits

Salary Range:

The salary range for this role is $120,000 - $160,000 per year, depending on experience and location. This estimate is based on market research for AI & Machine Learning Engineer roles in the Scottsdale, Arizona area, with adjustments for cost of living.

Benefits:

Competitive salary and 401k with employer match
Discretionary paid time off
Paid parental leave for all
Medical, Dental, Vision plans
Fitness Programs
Emotional & Mental Wellness support
Learning & Development programs
And yes, we have snacks in our offices

Working Hours:

This role requires a standard 40-hour workweek, with flexibility for deployment windows, maintenance, and project deadlines.

📝 Enhancement Note: The salary range provided is an estimate and should be verified with the hiring organization. Benefits may vary depending on the nature of your employment and the location where you work.

🎯 Team & Company Context

🏢 Company Culture

Industry:

Axon operates in the public safety technology industry, focusing on protecting life through innovative products and services.

Company Size:

Axon is a mid-sized company with a growing team of talented professionals dedicated to its mission of protecting life.

Founded:

Axon was founded in 1993 and has since grown to become a leader in the public safety technology sector.

Team Structure:

The AI & Machine Learning team at Axon consists of experienced professionals with a diverse range of skills and expertise.
The team works collaboratively with cross-functional teams, including data engineering, solution architecture, and business units, to support ongoing AI initiatives.

Development Methodology:

Axon employs Agile methodologies for software development, with a focus on iterative improvement and continuous delivery.
The team uses version control systems, such as Git, and CI/CD pipelines for automated deployment and testing.
Axon prioritizes security and compliance in its development processes, ensuring that all products and services meet the highest standards.

Company Website: Axon

📝 Enhancement Note: Axon’s company culture is characterized by its commitment to innovation, collaboration, and customer focus. The company values diversity, inclusion, and work-life balance, providing a supportive environment for its employees to grow and succeed.

📈 Career & Growth Analysis

AI & Machine Learning Career Level:

This role is at the Senior AI Platform Engineer II level, requiring a strong background in software development and a deep understanding of AI and machine learning technologies.
The role involves significant collaboration with cross-functional teams and requires strong communication and leadership skills.

Reporting Structure:

The Senior AI Platform Engineer II reports directly to the Senior Manager, Corporate AI Solutions.
The role works closely with data engineering, solution architecture, and business units to support ongoing AI initiatives.

Technical Impact:

The Senior AI Platform Engineer II plays a critical role in the deployment and integration of GPT-driven applications across various platforms and services.
The role requires a strong understanding of AI and machine learning technologies, as well as cloud platforms and security best practices.

Growth Opportunities:

Technical Skill Development: The role offers opportunities to learn and develop skills in AI and machine learning, with a focus on GPT and LLM deployment.
Technical Leadership: As the team grows, there may be opportunities to take on more significant technical leadership roles, driving architectural decisions and mentoring junior team members.
Career Progression: With experience and demonstrated success, there may be opportunities to advance to more senior roles within the AI & Machine Learning team or other areas of the organization.

📝 Enhancement Note: Axon provides numerous growth opportunities for its employees, with a strong focus on learning and development. The company encourages its team members to take on new challenges and expand their skills and knowledge.

🌐 Work Environment

Office Type:

Axon’s Scottsdale office is a modern, collaborative workspace designed to foster innovation and productivity.
The office features open-concept workspaces, meeting rooms, and breakout areas, with a focus on employee comfort and well-being.

Office Location(s):

Scottsdale, Arizona, United States
Other office locations include Seattle, Washington; San Francisco, California; Atlanta, Georgia; and Boston, Massachusetts.

Workspace Context:

Collaborative Work Environment: The office features open-concept workspaces that encourage collaboration and communication among team members.
Development Tools and Resources: Axon provides its employees with access to the latest development tools, multiple monitors, and testing devices to ensure optimal productivity.
Cross-Functional Collaboration: The office is designed to facilitate cross-functional collaboration between developers, designers, and stakeholders, with dedicated spaces for team meetings and brainstorming sessions.

Work Schedule:

This role follows a hybrid work arrangement, with employees working from the office and remotely as needed.
The work schedule is flexible, with a focus on delivering results and meeting project deadlines.
Deployment windows, maintenance, and other critical tasks may require employees to be available outside of standard business hours.

📝 Enhancement Note: Axon’s work environment is designed to be flexible and adaptable, with a focus on employee well-being and productivity. The company encourages its employees to maintain a healthy work-life balance and provides resources to support their physical and mental health.

📄 Application & Technical Interview Process

Interview Process:

Screening: A brief phone or video call to assess your qualifications and cultural fit for the role.
Technical Assessment: A hands-on coding challenge or project assessment to evaluate your technical skills and problem-solving abilities.
Behavioral Interview: A conversation to discuss your career aspirations, work style, and cultural fit with the team.
Final Interview: A meeting with the hiring manager and other team members to discuss your qualifications, answer any remaining questions, and make a final decision.

Portfolio Review Tips:

Highlight your software development projects, with a focus on AI and machine learning applications.
Include examples of your GPT or LLM integration projects, if available.
Demonstrate your understanding of cloud platforms and security best practices through your project documentation and code comments.

Technical Challenge Preparation:

Brush up on your programming skills, with a focus on Python, Java, JavaScript, and React.
Familiarize yourself with cloud platforms such as AWS, Azure, or GCP, and be prepared to discuss your experience with these technologies.
Review your understanding of AI and machine learning concepts, with a focus on GPT and LLM deployment.

📝 Enhancement Note: The interview process for this role is designed to be comprehensive and thorough, ensuring that the selected candidate is well-suited to the position and the team. Axon values transparency and communication throughout the interview process, providing clear feedback and guidance to all candidates.

🛠 Technology Stack & Web Infrastructure

Programming Languages:

Python, Java, JavaScript, React

Cloud Platforms:

AWS, Azure, GCP

AI & Machine Learning Libraries:

TensorFlow, PyTorch, Scikit-learn, Keras

Data Storage & Processing:

Snowflake, Apache Spark, Pandas

Version Control:

Git, GitHub, GitLab

CI/CD Pipelines:

Jenkins, CircleCI, GitHub Actions

Monitoring & Logging:

Prometheus, Grafana, ELK Stack

Containerization:

Docker, Kubernetes

Infrastructure as Code:

Terraform, CloudFormation

📝 Enhancement Note: Axon’s technology stack is designed to be flexible and adaptable, with a focus on leveraging the latest tools and technologies to drive innovation and productivity. The company encourages its employees to stay up-to-date with emerging trends and technologies in the AI & machine learning space.

👥 Team Culture & Values

AI & Machine Learning Values:

Innovation: Axon values innovation and encourages its employees to think creatively and push the boundaries of what is possible.
Collaboration: The company fosters a culture of collaboration, with a focus on working together to achieve common goals and drive success.
Customer Focus: Axon is committed to understanding and meeting the needs of its customers, with a focus on delivering high-quality products and services that make a meaningful impact.
Continuous Learning: The company encourages its employees to pursue continuous learning and professional development, with a focus on staying up-to-date with the latest trends and technologies in the AI & machine learning space.

Collaboration Style:

Cross-Functional Integration: The AI & Machine Learning team works closely with other teams, including data engineering, solution architecture, and business units, to support ongoing AI initiatives.
Code Review Culture: Axon prioritizes code review and peer programming practices to ensure code quality and maintainability.
Knowledge Sharing: The company encourages its employees to share their knowledge and expertise with their colleagues, fostering a culture of learning and growth.

📝 Enhancement Note: Axon’s team culture is characterized by its commitment to innovation, collaboration, and customer focus. The company values diversity, inclusion, and work-life balance, providing a supportive environment for its employees to grow and succeed.

⚡ Challenges & Growth Opportunities

Technical Challenges:

GPT Deployment: The role requires a strong understanding of GPT and LLM deployment, with a focus on integrating these technologies into existing systems and platforms.
Cloud Platform Integration: The role involves working with various cloud platforms, requiring a solid understanding of cloud architecture and best practices.
Security and Compliance: The role requires a strong understanding of security best practices and compliance standards, with a focus on protecting sensitive data and ensuring the integrity of AI systems.

Learning & Development Opportunities:

AI & Machine Learning Skill Development: The role offers opportunities to learn and develop skills in AI and machine learning, with a focus on GPT and LLM deployment.
Cloud Platform Proficiency: The role provides opportunities to expand your knowledge of cloud platforms and architecture, with a focus on AWS, Azure, and GCP.
Leadership and Mentoring: As the team grows, there may be opportunities to take on more significant technical leadership roles, driving architectural decisions and mentoring junior team members.

📝 Enhancement Note: Axon provides numerous growth opportunities for its employees, with a strong focus on learning and development. The company encourages its employees to take on new challenges and expand their skills and knowledge.

💡 Interview Preparation

Technical Questions:

AI & Machine Learning Fundamentals: Questions assessing your understanding of AI and machine learning concepts, with a focus on GPT and LLM deployment.
Cloud Platform Architecture: Questions evaluating your knowledge of cloud architecture and best practices, with a focus on AWS, Azure, and GCP.
Problem-Solving and Troubleshooting: Questions designed to assess your problem-solving skills and ability to diagnose and resolve technical issues.

Company & Culture Questions:

AI & Machine Learning Team Dynamics: Questions designed to evaluate your understanding of the AI & Machine Learning team’s goals, priorities, and work style.
Cross-Functional Collaboration: Questions assessing your ability to work effectively with other teams, including data engineering, solution architecture, and business units.
Customer Focus: Questions designed to evaluate your understanding of Axon’s customer base and the company’s commitment to delivering high-quality products and services.

Portfolio Presentation Strategy:

Project Selection: Choose projects that demonstrate your software development skills, with a focus on AI and machine learning applications.
Storytelling: Prepare a compelling narrative that highlights the challenges you faced, the solutions you implemented, and the outcomes you achieved.
Technical Deep Dive: Be prepared to discuss the technical aspects of your projects in detail, with a focus on GPT and LLM integration, cloud platform architecture, and security best practices.

📝 Enhancement Note: The interview process for this role is designed to be comprehensive and thorough, ensuring that the selected candidate is well-suited to the position and the team. Axon values transparency and communication throughout the interview process, providing clear feedback and guidance to all candidates.

📌 Application Steps

To apply for this Senior AI Platform Engineer II position at Axon:

Tailor Your Resume: Highlight your software development experience, with a focus on AI and machine learning projects.
Prepare Your Portfolio: Showcase your software development projects, with a focus on AI and machine learning applications.
Research Axon: Familiarize yourself with Axon’s mission, values, and company culture, and be prepared to discuss how your skills and experience align with the role and the team.
Prepare for Technical Interviews: Brush up on your programming skills, with a focus on Python, Java, JavaScript, and React.
Practice Coding Challenges: Familiarize yourself with cloud platforms such as AWS, Azure, or GCP, and be prepared to discuss your experience with these technologies.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Senior AI Platform Engineer II