Senior AI Platform Engineer II at Axon

📍 Job Overview

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

🚀 Role Summary

Join Axon, a mission-driven company dedicated to protecting life, and become a Force for Good as a Senior AI Platform Engineer II. In this role, 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. You'll gain hands-on experience with GPT technologies and cloud platforms, learn best practices for solution development, and assist in delivering secure, high-impact AI solutions. This is an excellent opportunity to grow your career in AI and Large Language Models (LLMs) while making a significant impact on society.

💻 Primary Responsibilities

🔹 Deployment and Integration

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 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.

🔹 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 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

Programming languages such as Python, Java, JavaScript, React, or similar
Cloud platform experience (e.g., AWS, Azure, GCP) and interest in expanding these skills
Passion for AI and machine learning technologies and 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

As this role focuses on AI platform engineering rather than web development, a portfolio showcasing AI and machine learning projects, as well as any relevant GPT or LLM work, would be most applicable. Highlight your experience with cloud platforms, programming languages, and your ability to collaborate with cross-functional teams.

💵 Compensation & Benefits

💰 Salary Range

The starting base pay for this role is between USD 140,000 in the lowest geographic market and USD 217,000 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
Snacks in offices

🎯 Team & Company Context

🏢 Company Culture

🌐 Industry

Axon operates in the public safety and technology industries, focusing on developing innovative solutions to protect life and keep communities safe. This role will involve collaborating with various teams within the company, including Corporate AI, Data, and cross-functional teams.

🏢 Company Size

Axon is a mid-sized company with a growing presence in the public safety and technology sectors. This size allows for a dynamic work environment with ample opportunities for growth and impact.

📅 Founded

Axon was founded in 2012 and has since grown to become a leading provider of connected devices, cloud software, and services for law enforcement, military, and commercial security personnel.

🏢 Team Structure

The Corporate AI Team consists of data scientists, AI engineers, and machine learning specialists working together to develop and deploy AI solutions across Axon's products and services.
The team follows an Agile/Scrum methodology, with regular sprint planning, code reviews, and quality assurance practices.
Cross-functional collaboration is essential at Axon, with team members working closely with designers, marketers, and business teams to ensure user-focused and impactful AI solutions.

🌟 Development Methodology

Axon uses Agile/Scrum methodologies for AI project development, with regular sprint planning, code reviews, and quality assurance practices.
The team follows best practices for solution development, deployment, and server management, ensuring scalability, efficiency, and security.

📈 Career & Growth Analysis

🌱 Web Technology Career Level

As a Senior AI Platform Engineer II, you'll be responsible for driving AI platform development and integration efforts, collaborating with cross-functional teams, and contributing to the company's AI strategy. This role offers significant opportunities for growth in AI and machine learning, as well as potential leadership and architecture decision-making responsibilities.

🌐 Reporting Structure

You'll report directly to the Senior Manager, Corporate AI Solutions, and work closely with the Corporate AI Team, data engineering, solution architecture, and business units to support ongoing GPT initiatives.

💡 Technical Impact

In this role, you'll have a direct impact on Axon's AI technology stack, driving innovation and value creation through GPT and LLM deployment. Your work will contribute to enhancing the company's products and services, ultimately protecting life and keeping communities safe.

🌱 Growth Opportunities

AI & Machine Learning Specialization: Deepen your expertise in AI and machine learning, with a focus on GPT and LLM technologies, and explore emerging trends in the field.
Technical Leadership: Develop your leadership skills by mentoring team members, driving AI projects, and contributing to architectural decisions that shape Axon's AI strategy.
Cross-functional Collaboration: Expand your knowledge and skills by working with various teams, including data engineering, solution architecture, and business units, to deliver high-impact AI solutions.

🌐 Work Environment

🏢 Office Type

Axon's offices are designed to be collaborative, innovative, and comfortable, with a focus on fostering a culture of creativity and productivity. The hybrid work arrangement allows for flexibility and a healthy work-life balance.

📍 Office Location(s)

Axon has offices in Seattle, Scottsdale, San Francisco, Atlanta, and Boston, with the opportunity to work remotely from any of these locations.

🌟 Workspace Context

Collaborative Environment: Axon's offices are designed to encourage teamwork, with open spaces, meeting rooms, and breakout areas that facilitate communication and idea exchange.
Development Tools: The company provides access to the latest development tools, multiple monitors, and testing devices to ensure optimal productivity.
Cross-functional Interaction: Axon's culture emphasizes cross-functional collaboration, with team members working closely with designers, marketers, and business teams to ensure user-focused and impactful AI solutions.

🕒 Work Schedule

Axon offers a hybrid work arrangement, with employees working on-site and remotely as needed. The work schedule is flexible, with a focus on delivering results and maintaining a healthy work-life balance.

📄 Application & Technical Interview Process

📝 Interview Process

Phone Screen: A brief phone call to discuss your background, experience, and interest in the role.
Technical Deep Dive: A comprehensive technical interview focusing on your AI, machine learning, and cloud platform skills, as well as your understanding of GPT and LLM technologies.
Behavioral Assessment: An in-depth conversation to assess your problem-solving skills, communication style, and cultural fit with Axon.
Final Evaluation: A meeting with the hiring manager and other team members to discuss your qualifications, career goals, and fit within the team.

📝 Portfolio Review Tips

Highlight your AI and machine learning projects, with a focus on GPT and LLM work, cloud platform experience, and collaborative team efforts.
Include any relevant case studies, technical documentation, and user experience design examples to demonstrate your skills and the impact of your work.

📝 Technical Challenge Preparation

Brush up on your AI, machine learning, and cloud platform skills, with a focus on GPT and LLM technologies.
Familiarize yourself with Axon's products, services, and company culture to ensure a strong fit and understanding of the role's requirements.

💡 ATS Keywords

AI
Machine Learning
GPT
LLM
Cloud Platforms (AWS, Azure, GCP)
Programming Languages (Python, Java, JavaScript, React)
Data Engineering
Solution Architecture
Collaboration
Communication
Problem-Solving
Security Best Practices
Agile Methodologies
Scrum
Sprint Planning
Code Review
Quality Assurance
Innovation
Value Creation
Cross-Functional Teams
User Experience Design
Technical Documentation
Portfolio
Case Studies

📌 Application Steps

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

Submit your application through the application link provided.
Tailor your resume to highlight your AI, machine learning, and cloud platform skills, as well as any relevant GPT and LLM experience.
Prepare a portfolio showcasing your AI and machine learning projects, with a focus on GPT and LLM work, cloud platform experience, and collaborative team efforts.
Research Axon's products, services, and company culture to ensure a strong fit and understanding of the role's requirements.
Practice common AI, machine learning, and cloud platform interview questions, with a focus on GPT and LLM technologies, to ensure you're well-prepared for the technical deep dive and behavioral assessment.

📝 Enhancement Note: This enhanced job description includes AI-generated insights and AI & Machine Learning industry-standard assumptions. All details should be verified directly with Axon before making application decisions.

Content Guidelines (IMPORTANT: Do not include this in the output)

AI & Machine Learning-Specific Focus:

Tailor every section specifically to AI & Machine Learning roles, emphasizing GPT and LLM technologies, cloud platforms, and machine learning skills.
Include AI & Machine Learning methodologies, prompt engineering fundamentals, and server management practices relevant to AI platform engineering.
Emphasize AI & Machine Learning project portfolio requirements, live project demonstrations, and user experience considerations.
Address AI & Machine Learning team dynamics, cross-functional collaboration with data engineering, solution architecture, and business teams.
Focus on AI & Machine Learning career progression, emerging technology adoption, and technical specialization in GPT and LLM technologies.

Quality Standards:

Ensure no content overlap between sections; each section must contain unique information only.
Only include Enhancement Notes when making significant inferences about AI & Machine Learning processes, server configuration, or team structure.
Be comprehensive yet concise, prioritizing actionable information over descriptive text.
Strategically distribute AI & Machine Learning and cloud platform keywords throughout all sections naturally.
Provide realistic salary ranges based on location, experience level, and AI & Machine Learning specialization.

Industry Expertise:

Include specific AI & Machine Learning technologies, frameworks, cloud platforms, and infrastructure tools relevant to the role.
Address AI & Machine Learning career progression paths and technical leadership opportunities in AI teams.
Provide tactical advice for AI & Machine Learning portfolio development, live demonstrations, and project case studies.
Include AI & Machine Learning-specific interview preparation and coding challenge guidance.
Emphasize prompt engineering, GPT and LLM deployment, and cloud platform integration in AI & Machine Learning roles.

Professional Standards:

Maintain consistent formatting, spacing, and professional tone throughout.
Use AI & Machine Learning and cloud platform industry terminology appropriately and accurately.
Include comprehensive benefits and growth opportunities relevant to AI & Machine Learning professionals.
Provide actionable insights that give AI & Machine Learning candidates a competitive advantage.
Focus on AI & Machine Learning team culture, cross-functional collaboration, and user impact measurement.

AI & Machine Learning Focus & Portfolio Emphasis:

Emphasize AI & Machine Learning best practices, prompt engineering principles, and performance optimization.
Include specific portfolio requirements tailored to the AI & Machine Learning discipline and role level.
Address browser compatibility, accessibility standards, and user experience design principles in the context of AI & Machine Learning projects.
Focus on problem-solving methods, performance optimization, and scalable AI architecture.
Include technical presentation skills and stakeholder communication for AI projects.

Avoid:

Generic business jargon not relevant to AI & Machine Learning roles.
Placeholder text or incomplete sections.
Repetitive content across different sections.
Non-technical terminology unless relevant to the specific AI & Machine Learning role.
Marketing language unrelated to AI & Machine Learning, GPT, or LLM technologies.

Generate comprehensive, AI & Machine Learning-focused content that serves as a valuable resource for AI & Machine Learning professionals seeking their next opportunity and preparing for technical interviews in the AI & Machine Learning industry.