City/State Virginia Beach, VA Work Shift Multiple shifts available Overview: Sentara is hiring a Senior MLOps & Generative AI Engineer! This position is fully remote! Candidates must reside in one of the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, or Wyoming. Overview We are seeking a highly skilled and experienced Senior MLOps & Generative AI Engineer to join our growing AI organization and help advance current and future initiatives applying machine learning, deep learning, NLP, and Generative AI technologies to improve healthcare outcomes and operational excellence. This role combines two critical focus areas: MLOps Engineering - building and scaling enterprise-grade ML infrastructure, deployment pipelines, observability, governance, and automation capabilities. Generative AI Engineering - designing, architecting, deploying, and optimizing secure, production-ready GenAI applications and platforms leveraging LLMs, RAG architectures, vector databases, prompt orchestration, and AI evaluation frameworks. As a Senior Engineer, you will partner closely with AI Scientists, Data Engineers, Software Engineers, Architects, and Product teams to operationalize AI/ML and Generative AI solutions at enterprise scale. You will play a key role in shaping the organization's AI platform strategy, driving best practices, and delivering scalable, secure, and reliable AI systems in production healthcare environments. Key Responsibilities MLOps Engineering Responsibilities Design, build, and maintain scalable ML infrastructure and pipelines supporting model training, deployment, monitoring, governance, and lifecycle management. Develop and optimize CI/CD pipelines for machine learning and AI workloads across development, staging, and production environments. Build reusable ML platform capabilities including feature stores, model registries, experimentation frameworks, artifact management, and deployment automation. Implement scalable orchestration and workflow solutions for batch and real-time ML inference workloads. Create robust monitoring systems to measure model performance, detect model drift, monitor data quality, and ensure production reliability. Develop automation tools and self-service capabilities to improve the efficiency, scalability, and reliability of MLOps processes. Collaborate with Data Scientists and Software Engineers to streamline the ML lifecycle from experimentation through enterprise production deployment. Apply software engineering best practices to AI/ML systems including testing, observability, resiliency, security, versioning, and infrastructure-as-code. Identify gaps and improvement opportunities within the organization's ML platform ecosystem and architect scalable solutions to address them. Support enterprise AI governance, compliance, auditability, and model risk management requirements. Ensure platform scalability, reliability, security, and operational excellence across AI/ML systems. Generative AI Engineering Responsibilities Lead the architecture, design, and deployment of enterprise Generative AI solutions leveraging LLMs, foundation models, and agentic AI systems. Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, semantic search, reranking, and retrieval optimization strategies. Build scalable LLM orchestration frameworks using technologies such as LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks. Develop advanced prompt engineering strategies, prompt chaining, context management, and agent workflows to improve LLM accuracy and reliability. Evaluate and implement fine-tuning, parameter-efficient tuning, and prompt-based optimization approaches for domain-specific use cases. Build AI evaluation and benchmarking frameworks to measure hallucination rates, response quality, grounding accuracy, toxicity, bias, latency, and business performance metrics. Implement AI safety guardrails, governance controls, content filtering, and responsible AI practices for enterprise healthcare environments. Design scalable GenAI APIs and microservices supporting high-throughput enterprise AI applications. Optimize GenAI systems for cost, latency, throughput, and inference performance across cloud and hybrid environments. Integrate enterprise data sources, healthcare systems, and knowledge repositories into secure GenAI workflows. Research and evaluate emerging GenAI technologies, open-source frameworks, and foundation models to drive innovation and continuous improvement. Develop architecture diagrams, technical roadmaps, implementation strategies, and executive-level documentation for enterprise AI initiatives. Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure and compliant deployment of GenAI solutions involving PHI and sensitive healthcare data. Contribute to the development of AI platform standards, reusable GenAI accelerators, templates, and engineering best practices. Required Qualifications 5+ years of experience building and deploying production software, ML systems, or AI platforms. 1+ years of hands-on experience building production Generative AI or LLM-based applications. Strong programming skills in Python and experience with software engineering best practices. Experience with major deep learning and LLM frameworks such as PyTorch, Hugging Face Transformers, TensorFlow, or equivalent. Hands-on experience implementing RAG architectures, vector search, embeddings, prompt engineering, and LLM orchestration frameworks. Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or equivalent technologies. Experience deploying AI/ML systems in cloud environments including AWS, Azure, or GCP. Strong understanding of APIs, distributed systems, microservices, and scalable backend architectures. Experience with Kubernetes, containerization, orchestration, and cloud-native infrastructure. Experience implementing CI/CD pipelines, infrastructure automation, and MLOps best practices. Experience building monitoring, observability, and alerting solutions for ML and AI systems. Strong understanding of AI/ML lifecycle management, governance, model versioning, and production operations. Experience designing secure, scalable, production-ready AI platforms and services. Strong communication and collaboration skills with the ability to work across technical and business teams. Preferred Qualifications Previous experience implementing Generative AI and MLOps solutions within healthcare environments. Experience working with EPIC or healthcare interoperability platforms. Understanding of HIPAA, PHI handling, healthcare compliance, and responsible AI practices. Experience with AI governance frameworks, LLM evaluation methodologies, and AI safety tooling. Experience with GPU infrastructure optimization and scalable inference architectures. Familiarity with multi-agent AI systems and autonomous workflows. Experience with event-driven architectures, streaming pipelines, and real-time inference systems. Exposure to model fine-tuning techniques including LoRA, PEFT, RLHF, or domain adaptation strategies. Experience with enterprise AI platform architecture and internal developer platforms. Prior experience mentoring engineers and leading technical initiatives. Education 5+ years of relevant experience with a degree (Required) or 7+ years of relevant experience without a degree (Required) Experience in lieu of Bachelor's Degree. Certification/Licensure No specific certification or licensure requirements Experience 5 to 7 years of relevant experience We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for Full Time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan . click apply for full job details
08/07/2026
Full time
City/State Virginia Beach, VA Work Shift Multiple shifts available Overview: Sentara is hiring a Senior MLOps & Generative AI Engineer! This position is fully remote! Candidates must reside in one of the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, or Wyoming. Overview We are seeking a highly skilled and experienced Senior MLOps & Generative AI Engineer to join our growing AI organization and help advance current and future initiatives applying machine learning, deep learning, NLP, and Generative AI technologies to improve healthcare outcomes and operational excellence. This role combines two critical focus areas: MLOps Engineering - building and scaling enterprise-grade ML infrastructure, deployment pipelines, observability, governance, and automation capabilities. Generative AI Engineering - designing, architecting, deploying, and optimizing secure, production-ready GenAI applications and platforms leveraging LLMs, RAG architectures, vector databases, prompt orchestration, and AI evaluation frameworks. As a Senior Engineer, you will partner closely with AI Scientists, Data Engineers, Software Engineers, Architects, and Product teams to operationalize AI/ML and Generative AI solutions at enterprise scale. You will play a key role in shaping the organization's AI platform strategy, driving best practices, and delivering scalable, secure, and reliable AI systems in production healthcare environments. Key Responsibilities MLOps Engineering Responsibilities Design, build, and maintain scalable ML infrastructure and pipelines supporting model training, deployment, monitoring, governance, and lifecycle management. Develop and optimize CI/CD pipelines for machine learning and AI workloads across development, staging, and production environments. Build reusable ML platform capabilities including feature stores, model registries, experimentation frameworks, artifact management, and deployment automation. Implement scalable orchestration and workflow solutions for batch and real-time ML inference workloads. Create robust monitoring systems to measure model performance, detect model drift, monitor data quality, and ensure production reliability. Develop automation tools and self-service capabilities to improve the efficiency, scalability, and reliability of MLOps processes. Collaborate with Data Scientists and Software Engineers to streamline the ML lifecycle from experimentation through enterprise production deployment. Apply software engineering best practices to AI/ML systems including testing, observability, resiliency, security, versioning, and infrastructure-as-code. Identify gaps and improvement opportunities within the organization's ML platform ecosystem and architect scalable solutions to address them. Support enterprise AI governance, compliance, auditability, and model risk management requirements. Ensure platform scalability, reliability, security, and operational excellence across AI/ML systems. Generative AI Engineering Responsibilities Lead the architecture, design, and deployment of enterprise Generative AI solutions leveraging LLMs, foundation models, and agentic AI systems. Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, semantic search, reranking, and retrieval optimization strategies. Build scalable LLM orchestration frameworks using technologies such as LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks. Develop advanced prompt engineering strategies, prompt chaining, context management, and agent workflows to improve LLM accuracy and reliability. Evaluate and implement fine-tuning, parameter-efficient tuning, and prompt-based optimization approaches for domain-specific use cases. Build AI evaluation and benchmarking frameworks to measure hallucination rates, response quality, grounding accuracy, toxicity, bias, latency, and business performance metrics. Implement AI safety guardrails, governance controls, content filtering, and responsible AI practices for enterprise healthcare environments. Design scalable GenAI APIs and microservices supporting high-throughput enterprise AI applications. Optimize GenAI systems for cost, latency, throughput, and inference performance across cloud and hybrid environments. Integrate enterprise data sources, healthcare systems, and knowledge repositories into secure GenAI workflows. Research and evaluate emerging GenAI technologies, open-source frameworks, and foundation models to drive innovation and continuous improvement. Develop architecture diagrams, technical roadmaps, implementation strategies, and executive-level documentation for enterprise AI initiatives. Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure and compliant deployment of GenAI solutions involving PHI and sensitive healthcare data. Contribute to the development of AI platform standards, reusable GenAI accelerators, templates, and engineering best practices. Required Qualifications 5+ years of experience building and deploying production software, ML systems, or AI platforms. 1+ years of hands-on experience building production Generative AI or LLM-based applications. Strong programming skills in Python and experience with software engineering best practices. Experience with major deep learning and LLM frameworks such as PyTorch, Hugging Face Transformers, TensorFlow, or equivalent. Hands-on experience implementing RAG architectures, vector search, embeddings, prompt engineering, and LLM orchestration frameworks. Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or equivalent technologies. Experience deploying AI/ML systems in cloud environments including AWS, Azure, or GCP. Strong understanding of APIs, distributed systems, microservices, and scalable backend architectures. Experience with Kubernetes, containerization, orchestration, and cloud-native infrastructure. Experience implementing CI/CD pipelines, infrastructure automation, and MLOps best practices. Experience building monitoring, observability, and alerting solutions for ML and AI systems. Strong understanding of AI/ML lifecycle management, governance, model versioning, and production operations. Experience designing secure, scalable, production-ready AI platforms and services. Strong communication and collaboration skills with the ability to work across technical and business teams. Preferred Qualifications Previous experience implementing Generative AI and MLOps solutions within healthcare environments. Experience working with EPIC or healthcare interoperability platforms. Understanding of HIPAA, PHI handling, healthcare compliance, and responsible AI practices. Experience with AI governance frameworks, LLM evaluation methodologies, and AI safety tooling. Experience with GPU infrastructure optimization and scalable inference architectures. Familiarity with multi-agent AI systems and autonomous workflows. Experience with event-driven architectures, streaming pipelines, and real-time inference systems. Exposure to model fine-tuning techniques including LoRA, PEFT, RLHF, or domain adaptation strategies. Experience with enterprise AI platform architecture and internal developer platforms. Prior experience mentoring engineers and leading technical initiatives. Education 5+ years of relevant experience with a degree (Required) or 7+ years of relevant experience without a degree (Required) Experience in lieu of Bachelor's Degree. Certification/Licensure No specific certification or licensure requirements Experience 5 to 7 years of relevant experience We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for Full Time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan . click apply for full job details
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. We are seeking a Staff Software Engineer to provide technical leadership across the CoverMyMeds Access Engineering portfolio. Reporting to the Senior Director of Access Engineering, this role operates across multiple engineering teams and product domains, driving architectural consistency, engineering excellence, and technical strategy. This is a highly influential individual contributor role focused on solving complex technical challenges, improving engineering effectiveness, and shaping the future of software development within Access Engineering. Success in this position is measured by organizational impact, technical leadership, and the outcomes enabled across teams rather than individual code contributions alone. What You'll Do Technical Leadership & Architecture Define and influence architectural direction across the Access Engineering portfolio. Lead technical strategy for initiatives that span multiple products, systems, and engineering teams. Evaluate architectural tradeoffs and guide teams toward scalable, maintainable solutions. Create reusable technical patterns, reference implementations, and engineering standards. Engineering Excellence Establish and promote best practices for software quality, reliability, security, observability, and maintainability. Help teams improve automated testing, production readiness, operational excellence, and system performance. Drive consistency in engineering practices while minimizing unnecessary complexity. Platform & Developer Productivity Identify opportunities to improve shared tooling, platform capabilities, and development workflows. Reduce technical friction and operational overhead, enabling engineers to focus on delivering customer value. Champion improvements that increase engineering velocity, quality, and sustainability. AI-Enabled Engineering Define and advance Access Engineering's strategy for AI-assisted software development and AI-enabled engineering practices. Partner with enterprise AI teams to adopt established standards while identifying use cases specific to Access Engineering. Evaluate tools, practices, and safeguards that support the responsible use of AI throughout the software development lifecycle. Technical Mentorship & Influence Mentor senior engineers and help strengthen technical leadership across the organization. Foster a culture of technical excellence, knowledge sharing, and continuous improvement. Influence engineering, product, and leadership stakeholders through technical expertise and strategic thinking. Hands-On Technical Contribution Remain actively engaged with implementation details to ensure architectural decisions are practical and executable. Contribute to software design, prototyping, troubleshooting, and critical development efforts when appropriate. Partner with engineering teams to solve complex technical and operational challenges. Priority will be given to candidates who reside in the Columbus, OH metropolitan area. We are unable to provide sponsorship for this role presently or in the future. Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, or a related technical field; equivalent practical experience considered. 10+ years of professional software engineering experience, including experience designing and building enterprise-scale software systems. Demonstrated experience leading technical initiatives across multiple teams, products, or organizational boundaries. Experience designing distributed systems, APIs, integration platforms, or cloud-native applications. Proven ability to influence technical direction without formal management authority. Experience mentoring engineers and driving engineering best practices. Critical & Required Skills The ideal candidate will demonstrate strong capabilities in the following areas: Software Architecture Enterprise application architecture Distributed systems design Microservices and service-oriented architectures API strategy and integration patterns Event-driven architectures System scalability and performance optimization Engineering Leadership Technical strategy and roadmap development Cross-team collaboration and influence Architectural governance and standards Technical decision-making and tradeoff analysis Leading large-scale, complex technical initiatives Software Quality & Reliability Automated testing strategies Observability and monitoring Site reliability principles Secure software development practices Production readiness and operational excellence Cloud & Modern Development Cloud-native architectures CI/CD and DevOps practices Infrastructure automation Modern software engineering practices Developer productivity and platform engineering concepts AI Readiness & Engineering Innovation Experience evaluating or implementing AI-assisted development tools Understanding of responsible AI practices and governance considerations Ability to identify practical AI use cases that improve engineering effectiveness Preferred Qualifications Experience in healthcare technology, health tech, pharmacy technology, payer technology, or regulated industries. Familiarity with prior authorization workflows, healthcare interoperability, or healthcare integrations. Experience supporting engineering organizations with 50+ developers across multiple products. Experience building developer platforms, shared services, or internal engineering tooling. Experience with architectural modernization initiatives involving legacy systems. Experience implementing engineering effectiveness metrics and software quality frameworks. Experience with AWS or other major cloud platforms. Prior experience serving as a Staff Engineer, Principal Engineer, Lead Architect, or equivalent senior individual contributor. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $155,300 - $258,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
08/07/2026
Full time
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. We are seeking a Staff Software Engineer to provide technical leadership across the CoverMyMeds Access Engineering portfolio. Reporting to the Senior Director of Access Engineering, this role operates across multiple engineering teams and product domains, driving architectural consistency, engineering excellence, and technical strategy. This is a highly influential individual contributor role focused on solving complex technical challenges, improving engineering effectiveness, and shaping the future of software development within Access Engineering. Success in this position is measured by organizational impact, technical leadership, and the outcomes enabled across teams rather than individual code contributions alone. What You'll Do Technical Leadership & Architecture Define and influence architectural direction across the Access Engineering portfolio. Lead technical strategy for initiatives that span multiple products, systems, and engineering teams. Evaluate architectural tradeoffs and guide teams toward scalable, maintainable solutions. Create reusable technical patterns, reference implementations, and engineering standards. Engineering Excellence Establish and promote best practices for software quality, reliability, security, observability, and maintainability. Help teams improve automated testing, production readiness, operational excellence, and system performance. Drive consistency in engineering practices while minimizing unnecessary complexity. Platform & Developer Productivity Identify opportunities to improve shared tooling, platform capabilities, and development workflows. Reduce technical friction and operational overhead, enabling engineers to focus on delivering customer value. Champion improvements that increase engineering velocity, quality, and sustainability. AI-Enabled Engineering Define and advance Access Engineering's strategy for AI-assisted software development and AI-enabled engineering practices. Partner with enterprise AI teams to adopt established standards while identifying use cases specific to Access Engineering. Evaluate tools, practices, and safeguards that support the responsible use of AI throughout the software development lifecycle. Technical Mentorship & Influence Mentor senior engineers and help strengthen technical leadership across the organization. Foster a culture of technical excellence, knowledge sharing, and continuous improvement. Influence engineering, product, and leadership stakeholders through technical expertise and strategic thinking. Hands-On Technical Contribution Remain actively engaged with implementation details to ensure architectural decisions are practical and executable. Contribute to software design, prototyping, troubleshooting, and critical development efforts when appropriate. Partner with engineering teams to solve complex technical and operational challenges. Priority will be given to candidates who reside in the Columbus, OH metropolitan area. We are unable to provide sponsorship for this role presently or in the future. Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, or a related technical field; equivalent practical experience considered. 10+ years of professional software engineering experience, including experience designing and building enterprise-scale software systems. Demonstrated experience leading technical initiatives across multiple teams, products, or organizational boundaries. Experience designing distributed systems, APIs, integration platforms, or cloud-native applications. Proven ability to influence technical direction without formal management authority. Experience mentoring engineers and driving engineering best practices. Critical & Required Skills The ideal candidate will demonstrate strong capabilities in the following areas: Software Architecture Enterprise application architecture Distributed systems design Microservices and service-oriented architectures API strategy and integration patterns Event-driven architectures System scalability and performance optimization Engineering Leadership Technical strategy and roadmap development Cross-team collaboration and influence Architectural governance and standards Technical decision-making and tradeoff analysis Leading large-scale, complex technical initiatives Software Quality & Reliability Automated testing strategies Observability and monitoring Site reliability principles Secure software development practices Production readiness and operational excellence Cloud & Modern Development Cloud-native architectures CI/CD and DevOps practices Infrastructure automation Modern software engineering practices Developer productivity and platform engineering concepts AI Readiness & Engineering Innovation Experience evaluating or implementing AI-assisted development tools Understanding of responsible AI practices and governance considerations Ability to identify practical AI use cases that improve engineering effectiveness Preferred Qualifications Experience in healthcare technology, health tech, pharmacy technology, payer technology, or regulated industries. Familiarity with prior authorization workflows, healthcare interoperability, or healthcare integrations. Experience supporting engineering organizations with 50+ developers across multiple products. Experience building developer platforms, shared services, or internal engineering tooling. Experience with architectural modernization initiatives involving legacy systems. Experience implementing engineering effectiveness metrics and software quality frameworks. Experience with AWS or other major cloud platforms. Prior experience serving as a Staff Engineer, Principal Engineer, Lead Architect, or equivalent senior individual contributor. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $155,300 - $258,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
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.
08/06/2026
Full time
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.
08/06/2026
Full time
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.
08/06/2026
Full time
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.
08/06/2026
Full time
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.
08/06/2026
Full time
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.
08/06/2026
Full time
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.
08/04/2026
Full time
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.
08/04/2026
Full time
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.
08/04/2026
Full time
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.
08/04/2026
Full time
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.
08/04/2026
Full time
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.
08/04/2026
Full time
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.
Tech Summary This principal-level individual contributor serves within Kaiser Permanente's Container Platform and Adoption Services organization and provides technical leadership for the enterprise container platform service spanning on-premises and public-cloud environments. The department's mission is to deliver a consistent, secure, resilient, and supportable platform experience that enables application modernization and scalable adoption across the organization. The Container Platform Engineering Lead sets the technical direction for platform engineering and establishes the reusable standards, architectural guardrails, automation approaches, and engineering practices needed to operate the service as one enterprise capability. The position leads complex designs for shared platforms, dedicated environments, application onboarding, developer tooling, data services, enterprise middleware, and other specialized workloads while remaining actively engaged in engineering and implementation. The role works across application delivery, cloud and infrastructure engineering, cybersecurity, networking, observability, reliability engineering, enterprise architecture, and external service providers to translate strategy and risk requirements into practical platform outcomes. Through design leadership, technical governance, mentoring, and partnership with the Operations Lead, this position reduces fragmented solutions, improves engineering quality and platform reliability, and creates the repeatable capabilities required to modernize mission-critical healthcare applications at enterprise scale. This principal-level individual contributor serves within Kaiser Permanente's Container Platform and Adoption Services organization and provides technical leadership for the enterprise container platform service spanning on-premises and public-cloud environments. The department's mission is to deliver a consistent, secure, resilient, and supportable platform experience that enables application modernization and scalable adoption across the organization. The Container Platform Engineering Lead sets the technical direction for platform engineering and establishes the reusable standards, architectural guardrails, automation approaches, and engineering practices needed to operate the service as one enterprise capability. The position leads complex designs for shared platforms, dedicated environments, application onboarding, developer tooling, data services, enterprise middleware, and other specialized workloads while remaining actively engaged in engineering and implementation. The role works across application delivery, cloud and infrastructure engineering, cybersecurity, networking, observability, reliability engineering, enterprise architecture, and external service providers to translate strategy and risk requirements into practical platform outcomes. Through design leadership, technical governance, mentoring, and partnership with the Operations Lead, this position reduces fragmented solutions, improves engineering quality and platform reliability, and creates the repeatable capabilities required to modernize mission-critical healthcare applications at enterprise scale. Job Summary: This senior level employee is primarily responsible for influencing and leveraging the technical direction of integrated business and/or enterprise application solutions and for serving as an expert for technical teams. This employee is accountable for ensuring software solutions are managed with full adherence to industry best practices. Essential Responsibilities: Drives the execution of multiple work streams by identifying customer and operational needs; developing and updating new procedures and policies; gaining cross-functional support for objectives and priorities; translating business strategy into actionable business requirements; obtaining and distributing resources; setting standards and measuring progress; removing obstacles that impact performance; guiding performance and developing contingency plans accordingly; solving highly complex issues; and influencing the completion of project tasks by others. Practices self-leadership and promotes learning in others by soliciting and acting on performance feedback; building collaborative, cross-functional relationships; communicating information and providing advice to drive projects forward; adapting to competing demands and new responsibilities; providing feedback to others, including upward feedback to leadership; influencing, mentoring, and coaching team members; fostering open dialogue amongst team members; evaluating and responding to the strengths and weaknesses of self and unit members; and adapting to and learning from change, difficulties, and feedback. Provides insight into recommendations for complex technical solutions that meet design and functional needs. Serves as an expert for innovative technical solutions that meet design and functional needs. Collaborates with architects and/or software consultants to ensure functional specifications are converted into flexible, scalable, and maintainable solution designs. Provides technical expertise for the development, configuration, or modification of integrated business and/or enterprise application solutions within various computing environments by providing insight, guidance, and an escalation point for the design and coding of component-based applications. Translates business requirements and functional specifications into physical program designs, code modules, stable application systems, and software solutions by partnering with Business Analysts and other team members to understand business needs and functional specifications. Leverages networks to drive collaboration between technical teams, architects, and/or software consultants, and ensure functional specifications are converted into flexible, scalable, and maintainable solution designs. Builds and maintains trusting relationships with internal customers, third party vendors, and senior management to ensure the alignment, buy-in, and support of diverse project stakeholders. Oversees the review and implementation of recommendations of technical solutions across multiple functions. Takes accountability for ensuring specific interfaces, methods, parameters, procedures, and functions support technical solutions and are aligned with architectural designs. Derives an overall strategy of data management, within an established Information Architecture, that supports the business model. Identifies information structures and detail to enable the development and secure operation of new information services. Takes overall responsibility for planning effective information storage, sharing, and publishing within the organization. Sets strategies for effective use of database technology taking account of the complex interrelations between hardware/software. Provides specialist expertise in the development, use, or operation of database management system tools and facilities. Provides expert knowledge in the selection, provision, and use of database architectures, software, and facilities, typically taking responsibility for a team of technical staff. Facilitates and serves as a technical expert for project teams throughout the release schedule of business and enterprise software solutions. Provides expertise and guidance to team members for systems incident responses for complex issues. Fosters and leverages partnerships with IT teams and vendors to ensure written code adheres to company architectural standards, design patterns, and technical specification. Maintains and enhances technical expertise and knowledge of industry trends by attending participating conferences, and developing a network with other IT industry experts. Leads consultation efforts to help ensure new and existing software solutions are developed with insight into industry best practices, strategies, and architectures. Provides expert technical advice and recommendations to others within the organization on matters related to software engineering, including market trends, and new programs and applications. Reviews and verifies resource estimates for complex technical design, coding, and testing efforts. Identifies specific interfaces, methods, parameters, procedures, and functions, as required, to support technical solutions, serving as an escalation point for complex or unresolved issues related to requirements translation. As part of the IT Engineering job family, this position is responsible for leveraging DEVOPS, and both Waterfall and Agile practices, to design, develop, and deliver resilient, secure, multi-channel, high-volume, high-transaction, on/off-premise, cloud-based solutions. Minimum Qualifications: Minimum six (6) years experience working on project(s) involving the implementation of solutions applying development life cycles (e.g., SDLC). Minimum four (4) years in a technical leadership role with or without direct reports. Bachelors degree in Computer Science, CIS, or related field and Minimum ten (10) years experience in software development or a related field. Additional equivalent work experience may be substituted for the degree requirement.
07/28/2026
Full time
Tech Summary This principal-level individual contributor serves within Kaiser Permanente's Container Platform and Adoption Services organization and provides technical leadership for the enterprise container platform service spanning on-premises and public-cloud environments. The department's mission is to deliver a consistent, secure, resilient, and supportable platform experience that enables application modernization and scalable adoption across the organization. The Container Platform Engineering Lead sets the technical direction for platform engineering and establishes the reusable standards, architectural guardrails, automation approaches, and engineering practices needed to operate the service as one enterprise capability. The position leads complex designs for shared platforms, dedicated environments, application onboarding, developer tooling, data services, enterprise middleware, and other specialized workloads while remaining actively engaged in engineering and implementation. The role works across application delivery, cloud and infrastructure engineering, cybersecurity, networking, observability, reliability engineering, enterprise architecture, and external service providers to translate strategy and risk requirements into practical platform outcomes. Through design leadership, technical governance, mentoring, and partnership with the Operations Lead, this position reduces fragmented solutions, improves engineering quality and platform reliability, and creates the repeatable capabilities required to modernize mission-critical healthcare applications at enterprise scale. This principal-level individual contributor serves within Kaiser Permanente's Container Platform and Adoption Services organization and provides technical leadership for the enterprise container platform service spanning on-premises and public-cloud environments. The department's mission is to deliver a consistent, secure, resilient, and supportable platform experience that enables application modernization and scalable adoption across the organization. The Container Platform Engineering Lead sets the technical direction for platform engineering and establishes the reusable standards, architectural guardrails, automation approaches, and engineering practices needed to operate the service as one enterprise capability. The position leads complex designs for shared platforms, dedicated environments, application onboarding, developer tooling, data services, enterprise middleware, and other specialized workloads while remaining actively engaged in engineering and implementation. The role works across application delivery, cloud and infrastructure engineering, cybersecurity, networking, observability, reliability engineering, enterprise architecture, and external service providers to translate strategy and risk requirements into practical platform outcomes. Through design leadership, technical governance, mentoring, and partnership with the Operations Lead, this position reduces fragmented solutions, improves engineering quality and platform reliability, and creates the repeatable capabilities required to modernize mission-critical healthcare applications at enterprise scale. Job Summary: This senior level employee is primarily responsible for influencing and leveraging the technical direction of integrated business and/or enterprise application solutions and for serving as an expert for technical teams. This employee is accountable for ensuring software solutions are managed with full adherence to industry best practices. Essential Responsibilities: Drives the execution of multiple work streams by identifying customer and operational needs; developing and updating new procedures and policies; gaining cross-functional support for objectives and priorities; translating business strategy into actionable business requirements; obtaining and distributing resources; setting standards and measuring progress; removing obstacles that impact performance; guiding performance and developing contingency plans accordingly; solving highly complex issues; and influencing the completion of project tasks by others. Practices self-leadership and promotes learning in others by soliciting and acting on performance feedback; building collaborative, cross-functional relationships; communicating information and providing advice to drive projects forward; adapting to competing demands and new responsibilities; providing feedback to others, including upward feedback to leadership; influencing, mentoring, and coaching team members; fostering open dialogue amongst team members; evaluating and responding to the strengths and weaknesses of self and unit members; and adapting to and learning from change, difficulties, and feedback. Provides insight into recommendations for complex technical solutions that meet design and functional needs. Serves as an expert for innovative technical solutions that meet design and functional needs. Collaborates with architects and/or software consultants to ensure functional specifications are converted into flexible, scalable, and maintainable solution designs. Provides technical expertise for the development, configuration, or modification of integrated business and/or enterprise application solutions within various computing environments by providing insight, guidance, and an escalation point for the design and coding of component-based applications. Translates business requirements and functional specifications into physical program designs, code modules, stable application systems, and software solutions by partnering with Business Analysts and other team members to understand business needs and functional specifications. Leverages networks to drive collaboration between technical teams, architects, and/or software consultants, and ensure functional specifications are converted into flexible, scalable, and maintainable solution designs. Builds and maintains trusting relationships with internal customers, third party vendors, and senior management to ensure the alignment, buy-in, and support of diverse project stakeholders. Oversees the review and implementation of recommendations of technical solutions across multiple functions. Takes accountability for ensuring specific interfaces, methods, parameters, procedures, and functions support technical solutions and are aligned with architectural designs. Derives an overall strategy of data management, within an established Information Architecture, that supports the business model. Identifies information structures and detail to enable the development and secure operation of new information services. Takes overall responsibility for planning effective information storage, sharing, and publishing within the organization. Sets strategies for effective use of database technology taking account of the complex interrelations between hardware/software. Provides specialist expertise in the development, use, or operation of database management system tools and facilities. Provides expert knowledge in the selection, provision, and use of database architectures, software, and facilities, typically taking responsibility for a team of technical staff. Facilitates and serves as a technical expert for project teams throughout the release schedule of business and enterprise software solutions. Provides expertise and guidance to team members for systems incident responses for complex issues. Fosters and leverages partnerships with IT teams and vendors to ensure written code adheres to company architectural standards, design patterns, and technical specification. Maintains and enhances technical expertise and knowledge of industry trends by attending participating conferences, and developing a network with other IT industry experts. Leads consultation efforts to help ensure new and existing software solutions are developed with insight into industry best practices, strategies, and architectures. Provides expert technical advice and recommendations to others within the organization on matters related to software engineering, including market trends, and new programs and applications. Reviews and verifies resource estimates for complex technical design, coding, and testing efforts. Identifies specific interfaces, methods, parameters, procedures, and functions, as required, to support technical solutions, serving as an escalation point for complex or unresolved issues related to requirements translation. As part of the IT Engineering job family, this position is responsible for leveraging DEVOPS, and both Waterfall and Agile practices, to design, develop, and deliver resilient, secure, multi-channel, high-volume, high-transaction, on/off-premise, cloud-based solutions. Minimum Qualifications: Minimum six (6) years experience working on project(s) involving the implementation of solutions applying development life cycles (e.g., SDLC). Minimum four (4) years in a technical leadership role with or without direct reports. Bachelors degree in Computer Science, CIS, or related field and Minimum ten (10) years experience in software development or a related field. Additional equivalent work experience may be substituted for the degree requirement.