📍 Job Overview

Job Title: Senior AI Platform Engineer II
Company: Axon
Location: Atlanta, Georgia, United States
Job Type: Hybrid
Category: AI & Machine Learning Engineer
Date Posted: June 18, 2025
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.
Develop and maintain connectors to enhance GPT functionalities within existing systems.
Support the creation of training materials and documentation to promote effective use of AI technologies.
Assist in architectural guidance and enable innovation by identifying new ways to apply GPT technologies for business value.

📝 Enhancement Note: This role offers a unique opportunity to gain hands-on experience with GPT technologies and cloud platforms while working on real-world AI solutions. The hybrid work arrangement allows for flexibility while collaborating with teams based in multiple locations.

💻 Primary Responsibilities

Deployment and Integration:
- Implement patterns for deploying GPT-driven applications across various platforms and services.
- Collaborate with teams 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.

📝 Enhancement Note: This role requires strong communication skills and the ability to work collaboratively in a fast-paced environment. The successful candidate will be able to balance technical responsibilities with effective communication and teamwork.

🎓 Skills & Qualifications

Education: A 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.

📝 Enhancement Note: While a Bachelor's degree is required, equivalent experience may be considered. The preferred skills listed are not required but would be beneficial for success in this role.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

A well-structured portfolio showcasing your software development projects, with a focus on AI and machine learning applications.
Examples of your ability to integrate AI technologies into existing systems and deploy them across various platforms.
Documentation demonstrating your understanding of GPT technologies, prompt engineering, and best practices for AI deployment.

Technical Documentation:

Detailed code comments and documentation standards for your AI projects.
Version control, deployment processes, and server configuration examples relevant to AI platforms.
Testing methodologies, performance metrics, and optimization techniques specific to AI and machine learning applications.

📝 Enhancement Note: While a portfolio is not explicitly required for this role, having one would demonstrate your technical skills and commitment to AI and machine learning. Focus on projects that showcase your ability to deploy and integrate AI technologies.

💵 Compensation & Benefits

Salary Range: $120,000 - $160,000 per year (based on experience and location)

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 our offices

Working Hours: Full-time (40 hours per week) with flexible scheduling for deployment windows, maintenance, and project deadlines.

📝 Enhancement Note: The salary range provided is an estimate based on market research for AI & Machine Learning Engineers in the Atlanta, Georgia area. Actual compensation may vary based on experience, skills, and other factors.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology, focusing on public safety and justice solutions.

Company Size: Medium-sized (approximately 2,000 employees)

Founded: 2002

Team Structure:

The Corporate AI Team consists of experienced professionals working on AI and machine learning technologies.
The team collaborates with cross-functional teams, including data engineering, solution architecture, and business units.
The role reports directly to the Senior Manager, Corporate AI Solutions.

Development Methodology:

Agile methodologies are used for GPT project development and deployment.
Code reviews, testing, and quality assurance practices are followed to ensure the delivery of high-quality AI solutions.
Deployment strategies, CI/CD pipelines, and server management are employed to maintain secure and efficient AI platforms.

Company Website: Axon

📝 Enhancement Note: Axon's company culture emphasizes innovation, collaboration, and a commitment to protecting life through its technology solutions. The team structure and development methodologies support a dynamic and efficient work environment for AI & Machine Learning Engineers.

📈 Career & Growth Analysis

AI & Machine Learning Engineer Career Level: This role is an intermediate position in the AI & Machine Learning Engineer career path, focusing on deployment, integration, and architectural guidance for GPT technologies.

Reporting Structure: The role reports directly to the Senior Manager, Corporate AI Solutions, with opportunities for collaboration with cross-functional teams and business units.

Technical Impact: The successful candidate will have a significant impact on the deployment and integration of GPT-driven applications, contributing to Axon's mission to protect life through innovative AI solutions.

Growth Opportunities:

Technical Skill Development: Gain hands-on experience with GPT technologies and cloud platforms, learning best practices for solution development and deployment.
Emerging Technology Adoption: Stay up-to-date with the latest trends in AI, machine learning, and cloud services, applying them to real-world use cases.
Technical Leadership Potential: Demonstrate strong technical skills and leadership potential by driving innovation and value creation through GPT technologies.

📝 Enhancement Note: This role offers a unique opportunity for AI & Machine Learning Engineers to gain experience with GPT technologies and cloud platforms while working on real-world AI solutions. The growth opportunities listed are tailored to the specific needs and goals of the role.

🌐 Work Environment

Office Type: Hybrid, with flexible work arrangements allowing for remote work and on-site collaboration.

Office Location(s): Seattle, Scottsdale, San Francisco, Atlanta, Boston

Workspace Context:

Collaborative workspaces that foster team interaction and knowledge sharing.
Access to development tools, multiple monitors, and testing devices to support AI project development and deployment.
Cross-functional collaboration opportunities with data engineering, solution architecture, and business teams.

Work Schedule: Full-time (40 hours per week) with flexible scheduling for deployment windows, maintenance, and project deadlines.

📝 Enhancement Note: The hybrid work environment at Axon allows for flexibility and collaboration, with access to the necessary tools and resources to support AI project development and deployment. The work schedule is designed to accommodate deployment windows, maintenance, and project deadlines.

📄 Application & Technical Interview Process

Interview Process:

Technical Preparation: Brush up on your AI and machine learning skills, with a focus on GPT technologies and cloud platforms. Familiarize yourself with Axon's products and company culture.
Technical Assessment: Participate in a technical assessment, demonstrating your ability to deploy and integrate AI technologies. This may include live coding exercises or case studies.
Architectural Discussion: Engage in a discussion about architectural approaches for GPT projects, showcasing your understanding of scalability and efficiency.
Final Evaluation: Demonstrate your ability to communicate technical insights effectively and collaborate with cross-functional teams.

Portfolio Review Tips:

Highlight your AI and machine learning projects, demonstrating your ability to deploy and integrate AI technologies.
Include examples of your ability to work collaboratively and effectively communicate technical concepts to non-technical stakeholders.
Showcase your understanding of GPT technologies, prompt engineering, and best practices for AI deployment.

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, and GCP, focusing on AI and machine learning services.
Prepare for architectural discussions by reviewing best practices for GPT project deployment and integration.

ATS Keywords: AI, Machine Learning, GPT, LLM, Cloud Platforms, AWS, Azure, GCP, Python, Java, JavaScript, React, Deployment, Integration, Architecture, Collaboration, Communication, Security, Best Practices, Training, Documentation, Innovation, Value Creation.

📝 Enhancement Note: The interview process for this role is designed to assess your technical skills and ability to collaborate with cross-functional teams. The portfolio review tips and technical challenge preparation strategies are tailored to help you succeed in the interview process.

🛠 Technology Stack & Web Infrastructure

AI & Machine Learning Technologies:

GPT Technologies: Familiarity with GPT-3, GPT-4, and other large language models is required.
Cloud Platforms: Experience with AWS, Azure, or GCP is preferred, with a focus on AI and machine learning services.
Programming Languages: Proficiency in Python, Java, JavaScript, and React is required.
Data Platforms: Familiarity with data platforms such as Snowflake or any data integration tools is preferred.

Development & DevOps Tools:

Version Control: Familiarity with Git and GitHub is required.
CI/CD Pipelines: Experience with CI/CD pipelines and deployment automation tools is preferred.
Monitoring Tools: Familiarity with monitoring tools for AI platforms is preferred.

📝 Enhancement Note: The technology stack for this role is focused on AI and machine learning technologies, with a strong emphasis on GPT technologies and cloud platforms. Familiarity with the required technologies is essential for success in this role.

👥 Team Culture & Values

AI & Machine Learning Values:

Innovation: Axon values innovation and encourages its team members to explore emerging AI and machine learning trends.
Collaboration: The team emphasizes collaboration and cross-functional teamwork to deliver high-quality AI solutions.
Quality: Axon is committed to delivering secure, efficient, and user-friendly AI platforms.
Continuous Learning: The team encourages its members to stay up-to-date with the latest AI and machine learning developments.

Collaboration Style:

Cross-Functional Integration: The AI team works closely with data engineering, solution architecture, and business teams to support ongoing AI initiatives.
Code Review Culture: Axon emphasizes code reviews and peer programming practices to ensure the delivery of high-quality AI solutions.
Knowledge Sharing: The team encourages knowledge sharing, technical mentoring, and continuous learning.

📝 Enhancement Note: Axon's AI team values innovation, collaboration, and continuous learning. The collaboration style emphasizes cross-functional teamwork and knowledge sharing to deliver high-quality AI solutions.

⚡ Challenges & Growth Opportunities

Technical Challenges:

GPT Deployment: Develop and maintain patterns for deploying GPT-driven applications across various platforms and services.
AI Integration: Collaborate with cross-functional teams to build and maintain connectors that enhance GPT functionalities within existing systems.
AI Security: Learn and help maintain secure procedures for managing GPT API keys, ensuring compliance with Axon’s security standards.
AI Monitoring: Assist in setting up monitoring and auditing processes to track usage and detect anomalies.

Learning & Development Opportunities:

Technical Skill Development: Gain hands-on experience with GPT technologies and cloud platforms, learning best practices for solution development and deployment.
Emerging Technology Adoption: Stay up-to-date with the latest trends in AI, machine learning, and cloud services, applying them to real-world use cases.
Technical Leadership Potential: Demonstrate strong technical skills and leadership potential by driving innovation and value creation through GPT technologies.

📝 Enhancement Note: The technical challenges and learning opportunities listed are tailored to the specific needs and goals of the AI & Machine Learning Engineer role at Axon. Addressing these challenges and pursuing these opportunities will contribute to your professional growth and success in the role.

💡 Interview Preparation

Technical Questions:

AI Fundamentals: Demonstrate your understanding of AI and machine learning concepts, with a focus on GPT technologies and cloud platforms.
Architectural Design: Showcase your ability to design scalable and efficient AI solutions, considering deployment and integration challenges.
Problem-Solving: Present your problem-solving approach, showcasing your ability to address technical challenges and deliver innovative AI solutions.

Company & Culture Questions:

Axon Culture: Demonstrate your understanding of Axon's company culture, emphasizing innovation, collaboration, and continuous learning.
AI Integration: Explain your approach to integrating AI technologies into existing systems, considering user experience and technical constraints.
User Experience Impact: Discuss your understanding of the user experience, highlighting your ability to deliver AI solutions that meet user needs and expectations.

Portfolio Presentation Strategy:

AI Project Showcase: Highlight your AI and machine learning projects, demonstrating your ability to deploy and integrate AI technologies.
Technical Walkthrough: Present a live demo of your AI projects, showcasing your technical skills and understanding of GPT technologies.
User Experience Demonstration: Include examples of your ability to work collaboratively and effectively communicate technical concepts to non-technical stakeholders.

📝 Enhancement Note: The interview preparation strategies listed are tailored to help you succeed in the AI & Machine Learning Engineer interview process at Axon. By addressing these strategies, you will be better equipped to demonstrate your technical skills and cultural fit for the role.

📌 Application Steps

To apply for this AI & Machine Learning Engineer position at Axon:

Tailor Your Portfolio: Highlight your AI and machine learning projects, demonstrating your ability to deploy and integrate AI technologies. Include examples of your ability to work collaboratively and effectively communicate technical concepts to non-technical stakeholders.
Optimize Your Resume: Emphasize your AI and machine learning skills, cloud platform experience, and problem-solving abilities. Include relevant keywords to improve your resume's visibility in applicant tracking systems.
Prepare for Technical Interviews: Brush up on your AI and machine learning skills, with a focus on GPT technologies and cloud platforms. Familiarize yourself with Axon's products and company culture. Participate in technical assessments and architectural discussions, showcasing your ability to deploy and integrate AI technologies.
Research Axon: Learn about Axon's products, company culture, and AI initiatives. Prepare for company-specific questions and demonstrate your enthusiasm for the role and the company's mission to protect life through innovative AI solutions.

⚠️ 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