14 jobs found

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.

Data Analyst/ML Engineer / Junior AI Developer - Build AI With Strong Foundations Machine learning and AI roles require more than enthusiasm. Employers want candidates who can code, work with data, understand model behavior, evaluate results, and explain decisions. For junior candidates, strong foundations in Python, SQL, statistics, and software thinking are essential. SynergisticIT is considering candidates interested in Python, machine learning, NLP, statistics, model evaluation, APIs, data pipelines, AI applications, and cloud deployment basics. This opportunity is a strong fit for candidates who want to build AI-related skills while staying grounded in practical software and data workflows. SynergisticIT JOPP is good for ML and AI candidates because it helps them build a profile employers can evaluate. Candidates can strengthen technical fundamentals, work on practical projects, prepare for technical and behavioral interviews, and improve resume positioning for junior AI, ML, data science, and programming roles. Since 2010, Synergisticit has helped thousands of candidates land full-time jobs at tech leaders like Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Intel, Paypal, JPMC, Wayfair, BOA, CITI and hundreds more with Job offers of $95k to $154k. Synergisticit focuses on closing the gap between your tech skills and what employers want now. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/Data Engineers/ Data Scientists, Machine Learning engineers for full time positions with clients. We Focus on Java /Full stack/Devops and Data Science /Data Engineers/Data analysts/BI Analysts/ Machine learning/AI candidates Ideal Candidates: Recent grads in CS, Engineering, Math, or Statistics with limited or no job experience Jobseekers who had layoffs due to Downsizing and want to get in demand tech stack Professionals seeking a career switch to tech Candidates with career gaps or lacking real-world experience Individuals looking to boost their skill portfolio for better job prospects Computer Science grads with limited or no job experience Students who recently finished their Bachelor's or Master's programs Those struggling to land interviews despite having experience please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates Technical Skills or Experience? Which one is important to get a Job? Please check below links: Synergisticit Industry Event videos (OCW, JavaOne, Gartner data Analytics): USA Today feature Discover JOPP: Contact: Build AI skills with practical career preparation- Contact us Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req. Resume submissions may be shared with our JOPP team database also. Please unsubscribe if contacted or if you don't want to be contacted please don't submit your resume.

Interviews and Job offers? Let's make it happen with a Process which works Since 2010, we've helped thousands of candidates land full-time jobs at tech leaders like Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Intel, Paypal, JPMC, Wayfair, BOA, CITI and hundreds more with Job offers of $95k to $154k. Synergisticit focuses on closing the gap between your tech skills and what employers want now. You're not alone-and you're not the problem. The reality? Most CS grads struggle to land interviews because their resumes look just like everyone else's. Employers want more than a diploma-they want proven, practical skills, real-world tools, and candidates who are ready to perform from day one. That's exactly what SynergisticIT delivers. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/Data Engineers/ Data Scientists, Machine Learning engineers for full time positions with clients. We Focus on Java /Full stack/Devops and Data Science /Data Engineers/Data analysts/BI Analysts/ Machine learning/AI candidates Ideal Candidates: Recent grads in CS, Engineering, Math, or Statistics with limited or no job experience Jobseekers who had layoffs due to Downsizing and want to get in demand tech stack Professionals seeking a career switch to tech Candidates with career gaps or lacking real-world experience Individuals looking to boost their skill portfolio for better job prospects Computer Science grads with limited or no job experience Students who recently finished their Bachelor's or Master's programs Those struggling to land interviews despite having experience Why do Tech Companies not Hire recent Computer Science Graduates Technical Skills or Experience? Which one is important to get a Job? Please check below links: Synergisticit Industry Event videos (OCW, JavaOne, Gartner data Analytics): USA Today feature Discover JOPP: Contact: See It. Believe It. Become It. Don't let a lack of interviews stall your career. Let's give hiring managers exactly what they're looking for-and then some. You've already done the hard part. Now, let's get you hired. Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req. Resume submissions may be shared with our JOPP team database also. Please unsubscribe if contacted or if you don't want to be contacted please don't submit your resume.

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.