📍 Job Overview

Job Title: Senior AI Platform Engineer II
Company: Axon
Location: Hybrid from Seattle OR Scottsdale OR San Francisco OR Atlanta OR Boston
Job Type: Full-Time
Category: AI & Machine Learning Engineer
Date Posted: 2025-06-18
Experience Level: 2-5 years
Remote Status: Hybrid

🚀 Role Summary

AI & Machine Learning Focus: This role is centered around AI and Large Language Models (LLMs), with a focus on GPT technologies and cloud platforms.
Collaboration & Integration: You'll collaborate with the Corporate AI and Data Teams, as well as cross-functional teams, to support the adoption and integration of AI technologies within Axon.
Hands-On Experience: Gain practical experience with GPT technologies, cloud platforms, and learn best practices for solution development.
Secure & High-Impact AI Solutions: Assist in delivering secure, high-impact AI solutions by maintaining secure procedures and setting up monitoring processes.

📝 Enhancement Note: This role offers a unique opportunity to work with cutting-edge AI technologies and gain hands-on experience in a fast-paced, collaborative environment. The hybrid work arrangement allows for flexibility while still fostering team collaboration and knowledge sharing.

💻 Primary Responsibilities

Deployment & 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.
Training & 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.
Architectural Guidance:
- Work with the Corporate AI Team and solution architects to understand architectural approaches for GPT projects.
- Assist in identifying potential design improvements to ensure scalability and efficiency.
Innovation & 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 & 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.

📝 Enhancement Note: This role requires a strong focus on collaboration and communication, as you'll be working with various teams to integrate and deploy AI technologies. Your ability to understand and adapt to different architectural approaches will be crucial for success in this role.

🎓 Skills & Qualifications

Education: A Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience) is required.

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 strong portfolio showcasing your software development skills, with a focus on AI and machine learning projects.
Examples of GPT or LLM integration projects, highlighting your ability to deploy and integrate AI technologies.
Case studies demonstrating your problem-solving skills, performance optimization, and user experience design.

Technical Documentation:

Detailed documentation of your AI and machine learning projects, including code quality, commenting, and version control.
Performance metrics, testing methodologies, and optimization techniques used in your projects.
Any relevant certifications or training materials related to AI and machine learning technologies.

📝 Enhancement Note: While a strong portfolio is essential for this role, it's equally important to demonstrate your ability to collaborate and communicate effectively with cross-functional teams. Highlight any projects where you've worked with diverse teams to integrate and deploy AI technologies successfully.

💵 Compensation & Benefits

Salary Range: The starting base pay for this role is between USD 140,000 in the lowest geographic market and USD 240,000 in the highest geographic market. The actual base pay is dependent upon many factors, such as level, function, training, transferable skills, work experience, business needs, geographic market, and often a combination of all these factors.

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

📝 Enhancement Note: While the salary range for this role is competitive, the benefits package offered by Axon is designed to support employees both professionally and personally. The focus on learning and development programs, as well as emotional and mental wellness support, demonstrates Axon's commitment to employee growth and well-being.

🎯 Team & Company Context

Company Culture: Axon is committed to protecting life and fostering a culture of innovation, collaboration, and continuous learning. The company values diversity, inclusion, and empowering employees to drive real change.

Team Structure:

The Corporate AI Team consists of experienced AI and machine learning engineers who collaborate with cross-functional teams to integrate and deploy AI technologies.
The team is structured to promote knowledge sharing, mentoring, and continuous learning, with a focus on driving business value through AI solutions.

Development Methodology:

Axon employs Agile methodologies, with a focus on sprint planning, code review, and quality assurance practices.
The company encourages a culture of experimentation, learning from failures, and continuous improvement.

Company Website: www.axon.com

📝 Enhancement Note: Axon's commitment to protecting life is reflected in its culture, values, and the work its employees do. The company's focus on innovation, collaboration, and continuous learning creates an environment where AI and machine learning engineers can thrive and make a meaningful impact.

📈 Career & Growth Analysis

AI & Machine Learning Career Level: This role is at the Senior Engineer level, with a focus on driving AI and machine learning initiatives, collaborating with cross-functional teams, and delivering high-impact solutions.

Reporting Structure: This role reports directly to the Senior Manager, Corporate AI Solutions, and works closely with the Corporate AI Team and other cross-functional teams.

Technical Impact: In this role, you'll have a significant impact on Axon's AI and machine learning capabilities, driving innovation and value creation through GPT technologies and cloud platforms.

Growth Opportunities:

Technical Growth: Deepen your expertise in AI and machine learning technologies, with a focus on GPT technologies and cloud platforms.
Leadership Development: Gain experience in managing projects, mentoring junior team members, and driving strategic initiatives.
Architecture & Design: Contribute to architectural decisions and design patterns for AI and machine learning solutions, ensuring scalability and efficiency.

📝 Enhancement Note: This role offers numerous growth opportunities, from technical skill development to leadership and architecture decision-making. By working closely with cross-functional teams and driving AI and machine learning initiatives, you'll have the chance to make a significant impact on Axon's technology stack and business value.

🌐 Work Environment

Office Type: Axon's hybrid work arrangement allows for flexibility, with employees working from various locations, including Seattle, Scottsdale, San Francisco, Atlanta, and Boston.

Office Location(s): Axon's offices are located in these cities, with employees having the option to work from home or on-site, depending on their role and preferences.

Workspace Context:

Collaboration: The hybrid work environment fosters collaboration, with team members working together both in-person and remotely.
Tools & Resources: Axon provides development teams with access to modern tools, multiple monitors, and testing devices to ensure optimal productivity.
Cross-Functional Interaction: The company encourages cross-functional interaction, with development teams working closely with designers, marketers, and other stakeholders to deliver user-centered solutions.

Work Schedule: Axon's hybrid work arrangement offers flexibility, with employees working from home or on-site as needed, with a focus on maintaining work-life balance and supporting employee well-being.

📝 Enhancement Note: Axon's hybrid work environment offers the best of both worlds, allowing employees to balance the benefits of working from home with the collaboration and interaction of an on-site office setting. The company's focus on employee well-being and work-life balance ensures that team members can thrive both personally and professionally.

📄 Application & Technical Interview Process

Interview Process:

Technical Preparation: Familiarize yourself with GPT technologies, cloud platforms, and AI deployment patterns. Brush up on your programming skills, with a focus on Python, Java, JavaScript, and React.
AI & Machine Learning Fundamentals: Review AI and machine learning concepts, with a focus on prompt engineering, natural language processing, and deep learning techniques.
Architecture & System Design: Prepare for architecture and system design questions, focusing on GPT technologies, cloud platforms, and data integration.
Communication & Collaboration: Practice communicating technical concepts clearly and effectively, both written and verbally. Prepare for case studies and scenario-based questions that assess your ability to work collaboratively in a fast-paced environment.

Portfolio Review Tips:

Curate Your Portfolio: Highlight your AI and machine learning projects, with a focus on GPT or LLM integration, performance optimization, and user experience design.
Live Demos: Prepare live demos of your projects, showcasing your ability to deploy and integrate AI technologies effectively.
Code Quality: Demonstrate your commitment to code quality, commenting, and version control practices.
Technical Documentation: Include detailed documentation of your projects, highlighting your problem-solving skills, performance optimization, and user experience design.

Technical Challenge Preparation:

Practice Coding Challenges: Familiarize yourself with AI and machine learning coding challenges, focusing on GPT technologies, cloud platforms, and data integration.
Time Management: Practice time management skills, ensuring you can complete coding challenges within the given timeframe.
Communication & Explanation: Prepare clear and concise explanations of your coding approach, architecture decisions, and any trade-offs you've made.

📝 Enhancement Note: The interview process for this role is designed to assess your technical skills, problem-solving abilities, and communication effectiveness. By preparing thoroughly and showcasing your AI and machine learning expertise, you'll have a strong chance of success in the interview process.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies:

React: A JavaScript library for building user interfaces, commonly used for web and mobile applications.
HTML & CSS: The building blocks of web development, used to structure and style web pages.
JavaScript: A programming language used to make web pages interactive and dynamic.

Backend & Server Technologies:

Python: A popular programming language used for server-side scripting, data analysis, and machine learning.
Java: A high-level, object-oriented programming language used for enterprise-level applications and server-side development.
Cloud Platforms (AWS, Azure, GCP): The infrastructure used to deploy and manage AI and machine learning models, as well as other web applications.

Development & DevOps Tools:

Version Control Systems (Git): Tools used to manage changes to source code, enabling collaboration and tracking of project history.
Continuous Integration/Continuous Deployment (CI/CD) Pipelines: Automated processes for building, testing, and deploying software applications.
Monitoring & Logging Tools (Prometheus, ELK Stack): Tools used to monitor the performance and health of web applications and infrastructure.

📝 Enhancement Note: While this role focuses on AI and machine learning technologies, a strong understanding of the underlying web development and server administration concepts is essential for success. Familiarize yourself with the relevant technologies, tools, and best practices to ensure you can contribute effectively to Axon's AI and machine learning initiatives.

👥 Team Culture & Values

AI & Machine Learning Values:

Innovation: Axon encourages a culture of innovation, with team members constantly exploring new AI and machine learning trends and techniques.
Collaboration: The company fosters a collaborative environment, with team members working together to integrate and deploy AI technologies effectively.
Continuous Learning: Axon prioritizes continuous learning and development, with team members encouraged to expand their skills and knowledge in AI and machine learning.
User-Centered Design: The company emphasizes user-centered design, with AI and machine learning solutions tailored to meet the needs of Axon's customers and users.

Collaboration Style:

Cross-Functional Integration: Axon encourages cross-functional collaboration, with AI and machine learning teams working closely with designers, marketers, and other stakeholders to deliver user-centered solutions.
Code Review & Peer Programming: The company promotes a culture of code review and peer programming, with team members working together to ensure code quality and knowledge sharing.
Mentoring & Knowledge Sharing: Axon values mentoring and knowledge sharing, with team members encouraged to share their expertise and support the growth of their colleagues.

📝 Enhancement Note: Axon's culture of innovation, collaboration, and continuous learning creates an environment where AI and machine learning engineers can thrive and make a meaningful impact. By working closely with cross-functional teams and focusing on user-centered design, you'll have the opportunity to drive business value and contribute to Axon's mission to protect life.

🌱 Challenges & Growth Opportunities

Technical Challenges:

GPT Technologies: Stay up-to-date with the latest developments in GPT technologies, and be prepared to adapt to new tools and techniques as they emerge.
Cloud Platforms: Expand your knowledge of cloud platforms (AWS, Azure, GCP) and their respective AI and machine learning services.
Data Integration: Develop expertise in data integration, ensuring that AI and machine learning models can access and process the data they need to function effectively.
Performance Optimization: Continuously optimize AI and machine learning models for performance, scalability, and cost-effectiveness.

Learning & Development Opportunities:

Technical Skill Development: Deepen your expertise in AI and machine learning technologies, with a focus on GPT technologies and cloud platforms.
Emerging Technologies: Stay current with emerging AI and machine learning trends, and explore how they can be applied to real-world use cases.
Leadership Development: Gain experience in managing projects, mentoring junior team members, and driving strategic initiatives.
Architecture & Design: Contribute to architectural decisions and design patterns for AI and machine learning solutions, ensuring scalability and efficiency.

📝 Enhancement Note: The technical challenges and learning opportunities in this role are vast and varied, offering AI and machine learning engineers the chance to grow both personally and professionally. By embracing these challenges and pursuing continuous learning, you'll be well-positioned to make a significant impact on Axon's AI and machine learning capabilities.

💡 Interview Preparation

Technical Questions:

GPT Technologies: Prepare for questions about GPT technologies, their deployment patterns, and integration with existing systems.
Cloud Platforms: Brush up on your knowledge of cloud platforms (AWS, Azure, GCP) and their respective AI and machine learning services.
Data Integration: Familiarize yourself with data integration techniques, and be prepared to discuss how you would ensure that AI and machine learning models have access to the data they need to function effectively.
Performance Optimization: Prepare for questions about performance optimization, scalability, and cost-effectiveness in AI and machine learning models.

Company & Culture Questions:

AI & Machine Learning Culture: Research Axon's AI and machine learning culture, and be prepared to discuss how you would contribute to and thrive in this environment.
Collaboration & Communication: Prepare for questions about your ability to collaborate effectively with cross-functional teams, communicate technical concepts clearly, and work in a fast-paced environment.
User-Centered Design: Familiarize yourself with Axon's focus on user-centered design, and be prepared to discuss how you would ensure that AI and machine learning solutions meet the needs of Axon's customers and users.

Portfolio Presentation Strategy:

Live Demos: Prepare live demos of your AI and machine learning projects, showcasing your ability to deploy and integrate AI technologies effectively.
Code Quality: Demonstrate your commitment to code quality, commenting, and version control practices.
Technical Documentation: Include detailed documentation of your projects, highlighting your problem-solving skills, performance optimization, and user experience design.

📝 Enhancement Note: The interview process for this role is designed to assess your technical skills, problem-solving abilities, and communication effectiveness. By preparing thoroughly and showcasing your AI and machine learning expertise, you'll have a strong chance of success in the interview process.

📌 Application Steps

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

Customize Your Portfolio: Tailor your portfolio to highlight your AI and machine learning projects, with a focus on GPT or LLM integration, performance optimization, and user experience design.
Resume Optimization: Optimize your resume for AI and machine learning roles, emphasizing your programming skills, cloud platform experience, and problem-solving abilities.
Technical Interview Preparation: Brush up on your technical skills, with a focus on GPT technologies, cloud platforms, and AI deployment patterns. Practice coding challenges and prepare for architecture and system design questions.
Company Research: Research Axon's AI and machine learning culture, and be prepared to discuss how you would contribute to and thrive in this environment. Familiarize yourself with the company's mission, values, and commitment to protecting life.

⚠️ 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