15 jobs found

Department Description: At Disney, we're storytellers. We make the impossible, possible. The Walt Disney Company (TWDC) is a world-class entertainment and technological leader. Walt's passion was to continuously envision new ways to move audiences around the world-a passion that remains our touchstone in an enterprise that stretches from theme parks, resorts and a cruise line to sports, news, movies and a variety of other businesses. Uniting each endeavor is a commitment to creating and delivering unforgettable experiences - and we're constantly looking for new ways to enhance these exciting experiences. The Enterprise Technology mission is to deliver technology solutions that align to business strategies while enabling enterprise efficiency and promoting cross-company collaborative innovation. Our group drives competitive advantage by enhancing our consumer experiences, enabling business growth, and advancing operational excellence. The Global Information Security (GIS) organization strives to secure the magic by employing best-in-class services to assess, prevent, detect, and respond to cyber threats that present risk to The Walt Disney Company. We enable the business by integrating enterprise and business segment-specific supported services to create a robust, efficient, and adaptable cybersecurity program. Our key objectives are to: Secure the Magic by protecting information systems and platforms. Reduce Risk by proactively assessing, preventing, and detecting to prevent harm to the Company and our Guests. Strengthen the business through optimizing execution, application, and technology used to protect the Company. Innovate by investing in core capabilities to enhance operational efficiency. Team Description: Our DevOps Platform Team builds and ships shared security infrastructure, governance tooling, and enterprise automation at scale - with a relentless focus on production quality and engineering craft. This team designs, develops and implements security automation tools and sites to help our customers focus on areas of risk. This role involves taking ownership of technical projects, collaborating with team members, and contributing to security automation initiatives What You'll Do: The Senior Security Engineer - Software Engineer will: Work within the Security Development and Design team that is responsible for protecting the network and company assets from any security threats or attacks through the development of security automation capabilities. Architect and implement code deployment pipelines using GitLab or similar CI/CD processes Design and optimize security tool deployments, introducing scalable processes across Cyber Security capabilities Collaborate effectively with cross-functional teams and contribute to Information Security team efforts across the broad spectrum of information security programs Design, develop, and implement reliable platforms needed to host Applications with security requirements Build, maintain, and improve runbooks for application support and incident response procedures Design and implement monitoring solutions for all aspects of applications, including alerting capabilities Communicate effectively with stakeholders and contribute to technical decision-making Take ownership of security automation projects and contribute to team initiatives Research and evaluate new technologies and security tools to enhance team capabilities Required Qualifications & Skills: 5+ years of experience with scripting languages like Python, Bash, and PowerShell with ability to build reliable automation Strong knowledge of OpenSearch, PostgreSQL, and other data storage platforms including basic optimization techniques Proficient knowledge of Infrastructure as Code tools (CloudFormation, Terraform, Azure Resource Manager, Google Deployment Manager) with experience managing multi-environment deployments Proven ability to learn and maintain cutting-edge skills across multiple technical areas (Unix/Linux, Application Security, Vulnerability Management, etc.) Experience with deployment of new software and maintenance of deployed software in production environments Strong analytical and problem-solving skills with ability to troubleshoot distributed systems Proven ability to design solutions for complex problems and contribute to process improvement initiatives Experience handling confidential information and understanding of security best practices Preferred Qualifications: Strong expertise in Cloud Platforms (AWS/GCP/Azure) with experience in cloud architecture Proficiency in Terraform with experience managing infrastructure across environments Python/YAML/JSON with backend development experience Designing and implementing CICD pipelines through Jenkins, GitLab, or other enterprise tools Container technologies (Kubernetes, Docker) and orchestration concepts Knowledge of security frameworks and compliance standards (SOC2, ISO 27001, NIST) Security scanning tools integration and vulnerability management platforms Monitoring and observability tools (Prometheus, Grafana, ELK stack) Understanding of network security concepts and implementation Required Education: Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience Relevant security certifications (CISSP, CISM, AWS Security, etc.) preferred . The hiring range for this position in Seattle, WA is $135,400-$181,600 and in Burbank, CA is $129,300-$173,300 per year and in Orlando, FL is $123,100-$165,100 . The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Department Description: At Disney, we're storytellers. We make the impossible, possible. The Walt Disney Company (TWDC) is a world-class entertainment and technological leader. Walt's passion was to continuously envision new ways to move audiences around the world-a passion that remains our touchstone in an enterprise that stretches from theme parks, resorts and a cruise line to sports, news, movies and a variety of other businesses. Uniting each endeavor is a commitment to creating and delivering unforgettable experiences - and we're constantly looking for new ways to enhance these exciting experiences. The Enterprise Technology mission is to deliver technology solutions that align to business strategies while enabling enterprise efficiency and promoting cross-company collaborative innovation. Our group drives competitive advantage by enhancing our consumer experiences, enabling business growth, and advancing operational excellence. The Global Information Security (GIS) organization strives to secure the magic by employing best-in-class services to assess, prevent, detect, and respond to cyber threats that present risk to The Walt Disney Company. We enable the business by integrating enterprise and business segment-specific supported services to create a robust, efficient, and adaptable cybersecurity program. Our key objectives are to: Secure the Magic by protecting information systems and platforms. Reduce Risk by proactively assessing, preventing, and detecting to prevent harm to the Company and our Guests. Strengthen the business through optimizing execution, application, and technology used to protect the Company. Innovate by investing in core capabilities to enhance operational efficiency. Team Description: Our DevOps Platform Team builds and ships shared security infrastructure, governance tooling, and enterprise automation at scale - with a relentless focus on production quality and engineering craft. This team designs, develops and implements security automation tools and sites to help our customers focus on areas of risk. This role involves taking ownership of technical projects, collaborating with team members, and contributing to security automation initiatives What You'll Do: The Senior Security Engineer - Software Engineer will: Work within the Security Development and Design team that is responsible for protecting the network and company assets from any security threats or attacks through the development of security automation capabilities. Architect and implement code deployment pipelines using GitLab or similar CI/CD processes Design and optimize security tool deployments, introducing scalable processes across Cyber Security capabilities Collaborate effectively with cross-functional teams and contribute to Information Security team efforts across the broad spectrum of information security programs Design, develop, and implement reliable platforms needed to host Applications with security requirements Build, maintain, and improve runbooks for application support and incident response procedures Design and implement monitoring solutions for all aspects of applications, including alerting capabilities Communicate effectively with stakeholders and contribute to technical decision-making Take ownership of security automation projects and contribute to team initiatives Research and evaluate new technologies and security tools to enhance team capabilities Required Qualifications & Skills: 5+ years of experience with scripting languages like Python, Bash, and PowerShell with ability to build reliable automation Strong knowledge of OpenSearch, PostgreSQL, and other data storage platforms including basic optimization techniques Proficient knowledge of Infrastructure as Code tools (CloudFormation, Terraform, Azure Resource Manager, Google Deployment Manager) with experience managing multi-environment deployments Proven ability to learn and maintain cutting-edge skills across multiple technical areas (Unix/Linux, Application Security, Vulnerability Management, etc.) Experience with deployment of new software and maintenance of deployed software in production environments Strong analytical and problem-solving skills with ability to troubleshoot distributed systems Proven ability to design solutions for complex problems and contribute to process improvement initiatives Experience handling confidential information and understanding of security best practices Preferred Qualifications: Strong expertise in Cloud Platforms (AWS/GCP/Azure) with experience in cloud architecture Proficiency in Terraform with experience managing infrastructure across environments Python/YAML/JSON with backend development experience Designing and implementing CICD pipelines through Jenkins, GitLab, or other enterprise tools Container technologies (Kubernetes, Docker) and orchestration concepts Knowledge of security frameworks and compliance standards (SOC2, ISO 27001, NIST) Security scanning tools integration and vulnerability management platforms Monitoring and observability tools (Prometheus, Grafana, ELK stack) Understanding of network security concepts and implementation Required Education: Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience Relevant security certifications (CISSP, CISM, AWS Security, etc.) preferred . The hiring range for this position in Seattle, WA is $135,400-$181,600 and in Burbank, CA is $129,300-$173,300 per year and in Orlando, FL is $123,100-$165,100 . The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Department Description: At Disney, we're storytellers. We make the impossible, possible. The Walt Disney Company (TWDC) is a world-class entertainment and technological leader. Walt's passion was to continuously envision new ways to move audiences around the world-a passion that remains our touchstone in an enterprise that stretches from theme parks, resorts and a cruise line to sports, news, movies and a variety of other businesses. Uniting each endeavor is a commitment to creating and delivering unforgettable experiences - and we're constantly looking for new ways to enhance these exciting experiences. The Enterprise Technology mission is to deliver technology solutions that align to business strategies while enabling enterprise efficiency and promoting cross-company collaborative innovation. Our group drives competitive advantage by enhancing our consumer experiences, enabling business growth, and advancing operational excellence. The Global Information Security (GIS) organization strives to secure the magic by employing best-in-class services to assess, prevent, detect, and respond to cyber threats that present risk to The Walt Disney Company. We enable the business by integrating enterprise and business segment-specific supported services to create a robust, efficient, and adaptable cybersecurity program. Our key objectives are to: Secure the Magic by protecting information systems and platforms. Reduce Risk by proactively assessing, preventing, and detecting to prevent harm to the Company and our Guests. Strengthen the business through optimizing execution, application, and technology used to protect the Company. Innovate by investing in core capabilities to enhance operational efficiency. Team Description: Our DevOps Platform Team builds and ships shared security infrastructure, governance tooling, and enterprise automation at scale - with a relentless focus on production quality and engineering craft. This team designs, develops and implements security automation tools and sites to help our customers focus on areas of risk. This role involves taking ownership of technical projects, collaborating with team members, and contributing to security automation initiatives What You'll Do: The Senior Security Engineer - Software Engineer will: Work within the Security Development and Design team that is responsible for protecting the network and company assets from any security threats or attacks through the development of security automation capabilities. Architect and implement code deployment pipelines using GitLab or similar CI/CD processes Design and optimize security tool deployments, introducing scalable processes across Cyber Security capabilities Collaborate effectively with cross-functional teams and contribute to Information Security team efforts across the broad spectrum of information security programs Design, develop, and implement reliable platforms needed to host Applications with security requirements Build, maintain, and improve runbooks for application support and incident response procedures Design and implement monitoring solutions for all aspects of applications, including alerting capabilities Communicate effectively with stakeholders and contribute to technical decision-making Take ownership of security automation projects and contribute to team initiatives Research and evaluate new technologies and security tools to enhance team capabilities Required Qualifications & Skills: 5+ years of experience with scripting languages like Python, Bash, and PowerShell with ability to build reliable automation Strong knowledge of OpenSearch, PostgreSQL, and other data storage platforms including basic optimization techniques Proficient knowledge of Infrastructure as Code tools (CloudFormation, Terraform, Azure Resource Manager, Google Deployment Manager) with experience managing multi-environment deployments Proven ability to learn and maintain cutting-edge skills across multiple technical areas (Unix/Linux, Application Security, Vulnerability Management, etc.) Experience with deployment of new software and maintenance of deployed software in production environments Strong analytical and problem-solving skills with ability to troubleshoot distributed systems Proven ability to design solutions for complex problems and contribute to process improvement initiatives Experience handling confidential information and understanding of security best practices Preferred Qualifications: Strong expertise in Cloud Platforms (AWS/GCP/Azure) with experience in cloud architecture Proficiency in Terraform with experience managing infrastructure across environments Python/YAML/JSON with backend development experience Designing and implementing CICD pipelines through Jenkins, GitLab, or other enterprise tools Container technologies (Kubernetes, Docker) and orchestration concepts Knowledge of security frameworks and compliance standards (SOC2, ISO 27001, NIST) Security scanning tools integration and vulnerability management platforms Monitoring and observability tools (Prometheus, Grafana, ELK stack) Understanding of network security concepts and implementation Required Education: Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience Relevant security certifications (CISSP, CISM, AWS Security, etc.) preferred . The hiring range for this position in Seattle, WA is $135,400-$181,600 and in Burbank, CA is $129,300-$173,300 per year and in Orlando, FL is $123,100-$165,100 . The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.

AI Platform Engineer AI Platform Engineering Full-Time Hybrid Onsite (3 days/week) The Opportunity MassMutual's AI Platform Engineering team is looking for a curious, motivated AI Platform Engineer to launch their engineering career on a high-performing team. This is an entry-level role built for recent graduates and early-career engineers. You will learn directly from experienced platform engineers, contribute to real initiatives from your first weeks, and steadily build the skills to help design, deploy, and operate the systems that power AI across the enterprise. We care less about everything you already know and more about how quickly you learn, how you approach problems, and how much you care about doing good engineering work. The Team This is a unique opportunity to join the team that builds and operates the AI platform powering MassMutual's AI initiatives. The team works at the intersection of cloud infrastructure, AI/ML systems, and developer experience-delivering the foundational capabilities that shape how the entire organization builds and deploys AI. We partner closely with AI engineering, product, and cloud engineering teams across the enterprise, and we invest in growth through a culture of peer learning, candid feedback, mentorship, and shared technical standards. It is a team where early-career engineers are set up to succeed: hard problems are made tractable through clear documentation, thoughtful onboarding, and engineers who genuinely enjoy teaching. The Impact Contribute to platform components-cloud infrastructure, AI serving layers, and developer tooling-under the guidance of senior engineers, growing your understanding of how the pieces fit together. Support the design and implementation of platform features such as the LLM gateway, model serving infrastructure, and integration patterns-writing code, tests, and documentation with regular feedback from your team. Learn the team's engineering standards by participating in design reviews and code reviews, and by pairing with more experienced engineers on real problems. Take ownership of well-scoped tasks within larger initiatives, delivering them to production with support and steadily taking on more scope over time. Help keep the platform healthy by learning reliability practices-monitoring, alerting, SLOs, and incident reviews-and pitching in on operational work. Build familiarity with governance and compliance concepts such as access management, audit logging, and AI usage policies, and why they matter to enterprise customers. Communicate clearly and ask good questions-sharing what you learn, flagging blockers early, and collaborating with teammates and partner teams. Invest in your own growth through mentorship, pairing, and continuous learning, with the goal of ramping toward greater technical independence. The Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or a related technical field Foundational understanding of cloud computing and exposure to at least one major cloud provider (AWS, GCP, or Azure) through coursework, labs, or projects as shown by coursework or certification. 2+ years experience in programming proficiency in at least one language such as Python, Go, Java, or a comparable language (this could include coursework, internship experience, bootcamp, etc). The Ideal Qualifications Professional experience preferred: Internships, co-ops, apprenticeships, academic projects, and substantial personal projects all count. Basic familiarity with version control (Git) and a willingness to learn CI/CD, containers (Docker/Kubernetes), and infrastructure-as-code. Curiosity about AI/ML systems and an interest in how models are deployed and served in production. Strong written and verbal communication and a genuine eagerness to learn from feedback. Hands-on exposure to Kubernetes, Docker, or Terraform through coursework, certifications, hackathons, or personal projects. Relevant entry-level certifications are a plus but not required-for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. Any hands-on experience with AI/ML frameworks or LLM APIs, even at a hobby or class-project level. A public portfolio or open-source contributions (e.g., GitHub) that show initiative and a habit of building. Experience collaborating on a team project such as a capstone, hackathon, or group assignment. Comfort with ambiguity and enthusiasm for learning quickly in a fast-moving space. What to Expect as Part of MassMutual and the Team Structured onboarding and a dedicated mentor to support your ramp-up and early growth Regular meetings with the AI Platform Engineering team Focused one-on-one meetings with your manager Networking opportunities including access to Asian, Hispanic/Latinx, African American, women, LGBTQIA+, veteran, and disability-focused Business Resource Groups Access to learning content on Degreed and other informational platforms A company with a strong and stable ethical business, industry-leading pay and benefits, where your ethics and integrity will be valued MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need. California residents: For detailed information about your rights under the California Consumer Privacy Act (CCPA), please visit our California Consumer Privacy Act Disclosures page.