We are a mission-driven technology startup transforming the way in-home care is delivered through innovative AI solutions. Our platform unifies signals from cameras, sensors, wearables, and connected devices to turn raw data into secure, real-time insights and closed-loop care actions; giving families peace of mind, seniors dignified independence, and providers the tools to deliver safer, more proactive care. We're a small, mission-driven team tackling one of the most important challenges of our time: helping people age safely and independently at home. If that excites you, we'd love to have you join us. ABOUT THE ROLE: We need a Technical Product Manager who can be our in-house lead, someone who partners with our existing AI engineer contractors to keep building, rather than just handing off specs and waiting. This isn't a traditional PM role. You'll be embedded across our portfolio of vertical businesses, working directly with contractors and teams, moving between projects as priorities shift. You'll own both the technical product thinking and the hands-on execution of prototypes, MVPs, internal tools, and integrations, especially in the early, resource-light stages before a project has its own dedicated engineering team. As the team grows, this role is expected to evolve into hiring and managing other builders - so we're looking for someone who can operate as a strong senior individual contributor now and step into people leadership as the portfolio scales. Reporting directly to the CEOå and Head of Product, you'll evaluate priorities, identify tradeoffs, and provide recommendations on product direction, technical decisions, and resource allocation across multiple initiatives. While the CEO retains final decision-making authority, you'll provide the analysis, recommendations, and operational leadership needed to keep projects moving efficiently and effectively. As our portfolio grows, this role will evolve from a senior individual contributor into a people leadership position. You'll help define and build the product function, with the opportunity to hire, mentor, and lead additional builders as the organization scales. WHAT YOU'LL OWN: Product Strategy Across Multiple Projects Partner with business unit leads to define product direction, technical scope, and priorities - often for ventures still finding product-market fit. Translate ambiguous, early-stage ideas into clear requirements, PRDs, and success metrics. Prioritize building now vs. later, given that resources are shared across the portfolio and every project is competing for the same attention. Support in building technical narratives for decks and funding rounds Hands-On Building Personally build MVPs, prototypes, and early product versions - this may mean writing code, configuring no-code/low-code tools, or standing up integrations, depending on the project. Ship fast, validate with real users or data, and iterate - favoring working software over polished documentation. Build the internal tools and lightweight automation that let small or nonexistent teams punch above their weight. Working Across a Portfolio Move between 2-4 active projects at a time, context-switching without losing momentum on any of them. Standardize just enough process (documentation, handoff notes, basic architecture decisions) that a project can survive you rotating off it. Identify patterns and reusable components across business units - no reason to rebuild the same login flow or admin panel five times. Communicate clearly and frequently with non-technical stakeholders who may not have visibility into the technical details. Judgment & Prioritization Triage constantly: with limited time and sometimes no dedicated team per project, you decide what gets your attention this week. Push back on scope creep and unrealistic timelines when a project's ambitions outpace its resourcing. Recognize when projects require additional resources and proactively recommend solutions. Validate the work and technical quality of our offshore teams Growing the Function As the portfolio scales, help define and build out the builder/product function - potentially hiring and managing additional Technical PMs or product engineers. QUALIFICATIONS: Required 6+ years in product management or a hybrid product/engineering role, with direct, hands-on building experience (not purely spec-writing) - scripting, front-end/back-end development, no-code platforms, or technical prototyping all count. Comfortable working on multiple unrelated projects simultaneously, often with incomplete information and no dedicated team. Strong technical fluency: able to read code, understand system architecture, and make informed build/buy/integrate decisions. Experience taking a product from zero to a working first version, ideally in an early-stage or startup environment. Excellent written and verbal communication - you'll be the connective tissue between technical execution and business stakeholders who don't share your context by default. Preferred Prior experience at a startup studio, venture builder, holding company, or multi-brand/multi-subsidiary organization. Familiarity with traditional engineering and AI no-code/low-code tools (Experience standing up projects that were later handed off to dedicated engineering teams. Background in a technical discipline (CS, engineering) or equivalent self-taught technical depth. Exposure to robotics; IoT is a nice-to-have, not a requirement. WHAT SUCCESS LOOKS LIKE: Multiple projects have working, validated product versions that started as your prototypes or the support you've given other builders. Business unit leads trust you to make the right call on scope and priority without hand-holding. Projects you've rotated off of continue running smoothly because you left them in a maintainable state. Leadership has a clear, current picture of which projects are gaining traction and which need investment or should be sunset, informed by your product judgment. You've laid the groundwork to bring on and manage additional builders as the portfolio grows. A NOTE TO FIT: This role suits someone who gets energy from variety and ambiguity, not someone who wants deep, singular focus on one product for years. We value curiosity, ownership, humility, speed, and thoughtful debate. Strong opinions are welcome, and they should be backed by data and a willingness to adapt. The pay range for this role is: 100,000 - 150,000 USD per year(Culver City, CA) PI3f235fb0e9eb-4744
08/07/2026
Full time
We are a mission-driven technology startup transforming the way in-home care is delivered through innovative AI solutions. Our platform unifies signals from cameras, sensors, wearables, and connected devices to turn raw data into secure, real-time insights and closed-loop care actions; giving families peace of mind, seniors dignified independence, and providers the tools to deliver safer, more proactive care. We're a small, mission-driven team tackling one of the most important challenges of our time: helping people age safely and independently at home. If that excites you, we'd love to have you join us. ABOUT THE ROLE: We need a Technical Product Manager who can be our in-house lead, someone who partners with our existing AI engineer contractors to keep building, rather than just handing off specs and waiting. This isn't a traditional PM role. You'll be embedded across our portfolio of vertical businesses, working directly with contractors and teams, moving between projects as priorities shift. You'll own both the technical product thinking and the hands-on execution of prototypes, MVPs, internal tools, and integrations, especially in the early, resource-light stages before a project has its own dedicated engineering team. As the team grows, this role is expected to evolve into hiring and managing other builders - so we're looking for someone who can operate as a strong senior individual contributor now and step into people leadership as the portfolio scales. Reporting directly to the CEOå and Head of Product, you'll evaluate priorities, identify tradeoffs, and provide recommendations on product direction, technical decisions, and resource allocation across multiple initiatives. While the CEO retains final decision-making authority, you'll provide the analysis, recommendations, and operational leadership needed to keep projects moving efficiently and effectively. As our portfolio grows, this role will evolve from a senior individual contributor into a people leadership position. You'll help define and build the product function, with the opportunity to hire, mentor, and lead additional builders as the organization scales. WHAT YOU'LL OWN: Product Strategy Across Multiple Projects Partner with business unit leads to define product direction, technical scope, and priorities - often for ventures still finding product-market fit. Translate ambiguous, early-stage ideas into clear requirements, PRDs, and success metrics. Prioritize building now vs. later, given that resources are shared across the portfolio and every project is competing for the same attention. Support in building technical narratives for decks and funding rounds Hands-On Building Personally build MVPs, prototypes, and early product versions - this may mean writing code, configuring no-code/low-code tools, or standing up integrations, depending on the project. Ship fast, validate with real users or data, and iterate - favoring working software over polished documentation. Build the internal tools and lightweight automation that let small or nonexistent teams punch above their weight. Working Across a Portfolio Move between 2-4 active projects at a time, context-switching without losing momentum on any of them. Standardize just enough process (documentation, handoff notes, basic architecture decisions) that a project can survive you rotating off it. Identify patterns and reusable components across business units - no reason to rebuild the same login flow or admin panel five times. Communicate clearly and frequently with non-technical stakeholders who may not have visibility into the technical details. Judgment & Prioritization Triage constantly: with limited time and sometimes no dedicated team per project, you decide what gets your attention this week. Push back on scope creep and unrealistic timelines when a project's ambitions outpace its resourcing. Recognize when projects require additional resources and proactively recommend solutions. Validate the work and technical quality of our offshore teams Growing the Function As the portfolio scales, help define and build out the builder/product function - potentially hiring and managing additional Technical PMs or product engineers. QUALIFICATIONS: Required 6+ years in product management or a hybrid product/engineering role, with direct, hands-on building experience (not purely spec-writing) - scripting, front-end/back-end development, no-code platforms, or technical prototyping all count. Comfortable working on multiple unrelated projects simultaneously, often with incomplete information and no dedicated team. Strong technical fluency: able to read code, understand system architecture, and make informed build/buy/integrate decisions. Experience taking a product from zero to a working first version, ideally in an early-stage or startup environment. Excellent written and verbal communication - you'll be the connective tissue between technical execution and business stakeholders who don't share your context by default. Preferred Prior experience at a startup studio, venture builder, holding company, or multi-brand/multi-subsidiary organization. Familiarity with traditional engineering and AI no-code/low-code tools (Experience standing up projects that were later handed off to dedicated engineering teams. Background in a technical discipline (CS, engineering) or equivalent self-taught technical depth. Exposure to robotics; IoT is a nice-to-have, not a requirement. WHAT SUCCESS LOOKS LIKE: Multiple projects have working, validated product versions that started as your prototypes or the support you've given other builders. Business unit leads trust you to make the right call on scope and priority without hand-holding. Projects you've rotated off of continue running smoothly because you left them in a maintainable state. Leadership has a clear, current picture of which projects are gaining traction and which need investment or should be sunset, informed by your product judgment. You've laid the groundwork to bring on and manage additional builders as the portfolio grows. A NOTE TO FIT: This role suits someone who gets energy from variety and ambiguity, not someone who wants deep, singular focus on one product for years. We value curiosity, ownership, humility, speed, and thoughtful debate. Strong opinions are welcome, and they should be backed by data and a willingness to adapt. The pay range for this role is: 100,000 - 150,000 USD per year(Culver City, CA) PI3f235fb0e9eb-4744
About the job Who we are: Circuit Check is the market-leading provider of automated test systems and test fixtures for complex electronic products for the automotive, military/aerospace, medical, industrial, and computer networking industries. At Circuit Check, we believe that innovation is a must, and that a challenging and robust environment where the work is consistently new and cutting edge is the best way to foster creativity. If you are ready to further your career in a fast-paced, technology driven organization where our test designs impact products that are used by millions of people around the world every day, then we invite you to join us at Circuit Check.Our design staff includes electrical, software, mechanical engineers, and project managers. Our systems are supported by staff throughout the United States, Canada, Mexico, Europe, Malaysia, and China. Primary Objective Lead the strategic development and growth of Circuit Check's most significant customer relationships in the AI/ML data center infrastructure market. Architect and execute multi-year account strategies that drive large-scale program wins, deepen executive-level partnerships, and position the company as the preferred technology partner for hyperscale and enterprise AI customers. This role does not carry a traditional sales quota; compensation includes bonus objectives tied to winning new large customers, capturing major programs, and expanding strategic account revenue. Major Areas of Accountability Strategic Account Leadership Develop and own multi-year strategic account plans for the company's largest AI/ML infrastructure customers, anticipating market shifts and positioning ahead of competitive threats Analyze customer technology roadmaps, capital expenditure patterns, and buying dynamics to identify high-value opportunities across GPU test, thermal management, power delivery, and related segments Serve as the primary executive-level interface with strategic accounts, building trusted advisor relationships with VP and C-suite decision-makers at hyperscale cloud providers, AI chipmakers, and data center operators Take decisive ownership of high-stakes negotiations, complex proposals, and multi-million-dollar program pursuits, differentiating Circuit Check solutions Cross-Functional Program Orchestration Coordinate engineering, product management and operations around customer requirements Partner with Product Line Managers to translate customer insights into product roadmap inputs aligned with AI/ML market direction Drive program management cadence for strategic accounts: pipeline reviews, executive business reviews, win/loss analysis, and quarterly assessments Market Intelligence & Growth Strategy Identify patterns in AI/ML technology adoption, supply chain shifts, and customer investment priorities that create strategic openings for Circuit Check Quantify new market opportunities through analysis of TAM, competitive dynamics, segment profitability, and technology adjacencies; present data-supported recommendations to senior leadership Build and maintain industry relationships across the AI/ML ecosystem, including suppliers, contract manufacturers, analysts, and technology partners worldwide International Business Development Develop and execute customer engagement strategies in key AI/ML hubs, with emphasis on Silicon Valley and Taiwan Navigate international business environments including multi-stakeholder decision processes and cultural dynamics across Asia-Pacific Represent the company at international conferences, trade shows, and executive briefings as an authoritative voice on AI/ML infrastructure Sales Team Collaboration & Mentorship Mentor less experienced sales team members on complex deal strategy, multi-stakeholder navigation, and executive engagement Partner with assigned account team members who maintain day-to-day relationships, providing strategic direction while developing their capabilities Collaborate with Sales Leadership to build playbooks and best practices for pursuing large AI/ML infrastructure programs Education & Experience Bachelor's degree in Engineering (Electrical, Mechanical, or related) required; MBA or advanced technical degree preferred 10+ years of progressive experience in strategic account management, business development, or program leadership in semiconductor, electronic hardware, test & measurement, data center infrastructure, or related technology sectors Track record of winning and managing multi-million-dollar programs with complex, multi-stakeholder customer organizations Strongly preferred: executive-level relationships at hyperscale cloud providers; experience in the AI/ML hardware ecosystem (GPU test/validation, liquid cooling, power distribution, rack-scale integration, or related infrastructure) International business experience preferred, especially in the Taiwan semiconductor ecosystem and/or SE Asian manufacturing Knowledge, Skills & Abilities Strategic & Analytical Thinking Ability to see patterns across complex data, customer behaviors, and market signals - and translate insights into actionable strategies and business cases Rigorous analytical skills: financial models, program economics, pricing structures, and competitive intelligence that inform decision-making Thinks several moves ahead - anticipating customer needs, competitive responses, and market evolution Organizational & Execution Leadership Natural ability to orchestrate multiple moving parts - people, timelines, resources, priorities - across complex programs and matrixed organizations Skilled at configuring cross-functional teams for maximum effectiveness, with the program management discipline to track interdependencies and keep engagements on schedule and budget Presence & Influence Commanding executive presence with confidence to lead negotiations, challenge the status quo, and drive decisions in ambiguous situations Willingness to take charge, confront difficult issues directly, and provide clear direction when the path forward is uncertain Exceptional communication skills - compelling narratives, proposals, and presentations for technical and executive audiences Industry & Technical Acumen Deep understanding of the AI/ML data center ecosystem: GPU architectures, training/inference infrastructure, thermal management, power delivery, rack integration, and test/validation Credible in technical discussions with customer engineering teams while maintaining a business-outcome focus; proficient with CRM platforms (Salesforce preferred) Compensation & Performance Structure This role does not carry a traditional sales quota. Compensation includes a competitive base salary plus bonus objectives tied to: Winning new strategic AI/ML customers and capturing large new programs with existing accounts Growth in strategic account revenue and program pipeline value Program execution milestones and customer satisfaction metrics Location & Travel Requirements Open to remote candidates in the United States, with a preference for candidates in the San Francisco Bay Area, California Travel expected up to 50%, including customer visits throughout the Bay Area, across the US, and periodic international travel to Taiwan and SE Asia Must possess a valid passport and ability to obtain required travel visas Physical Requirements These physical requirements must be performed with or without accommodation: Time split between office/home office, customer sites, and travel Ability to sit for extended periods; bend, reach, stoop, and twist as required Heavy computer use; occasional exposure to manufacturing or lab environments Ability to lift and carry up to 25 lbs This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required of the employee. Duties, responsibilities, and activities may change at any time with or without notice. Pay and Benefits This job description reflects management's assignment of key responsibilities; it does not prescribe or restrict the tasks that may be assigned. Base pay is only one element of an employee's total compensation at Circuit Check. Employees (and their dependents in most plans) are covered by medical, dental, vision, basic life, short- and long-term disability and accidental death and dismemberment insurance. Employees are able to enroll in Circuit Check's 401k plan, in which the Company will match 50% of your contributions up to 6% with a maximum contribution. Paid time off includes vacation and sick time along with paid holidays. A summary of benefits can be provided by request via email to . Circuit Check, Inc. is proud to be an Equal Opportunity Employer. We do not discriminate based on identity, race, color, religion, national origin or ancestry, sex (including sexual identity), age, physical or mental disability, pregnancy, veteran or military status, genetic information, sexual orientation, marital status, or any other legally recognized protected basis under federal, state, or local law. Because Circuit Check is a federal contractor, we participate in the E-Verify program in certain locations, as required by law . click apply for full job details
08/07/2026
Full time
About the job Who we are: Circuit Check is the market-leading provider of automated test systems and test fixtures for complex electronic products for the automotive, military/aerospace, medical, industrial, and computer networking industries. At Circuit Check, we believe that innovation is a must, and that a challenging and robust environment where the work is consistently new and cutting edge is the best way to foster creativity. If you are ready to further your career in a fast-paced, technology driven organization where our test designs impact products that are used by millions of people around the world every day, then we invite you to join us at Circuit Check.Our design staff includes electrical, software, mechanical engineers, and project managers. Our systems are supported by staff throughout the United States, Canada, Mexico, Europe, Malaysia, and China. Primary Objective Lead the strategic development and growth of Circuit Check's most significant customer relationships in the AI/ML data center infrastructure market. Architect and execute multi-year account strategies that drive large-scale program wins, deepen executive-level partnerships, and position the company as the preferred technology partner for hyperscale and enterprise AI customers. This role does not carry a traditional sales quota; compensation includes bonus objectives tied to winning new large customers, capturing major programs, and expanding strategic account revenue. Major Areas of Accountability Strategic Account Leadership Develop and own multi-year strategic account plans for the company's largest AI/ML infrastructure customers, anticipating market shifts and positioning ahead of competitive threats Analyze customer technology roadmaps, capital expenditure patterns, and buying dynamics to identify high-value opportunities across GPU test, thermal management, power delivery, and related segments Serve as the primary executive-level interface with strategic accounts, building trusted advisor relationships with VP and C-suite decision-makers at hyperscale cloud providers, AI chipmakers, and data center operators Take decisive ownership of high-stakes negotiations, complex proposals, and multi-million-dollar program pursuits, differentiating Circuit Check solutions Cross-Functional Program Orchestration Coordinate engineering, product management and operations around customer requirements Partner with Product Line Managers to translate customer insights into product roadmap inputs aligned with AI/ML market direction Drive program management cadence for strategic accounts: pipeline reviews, executive business reviews, win/loss analysis, and quarterly assessments Market Intelligence & Growth Strategy Identify patterns in AI/ML technology adoption, supply chain shifts, and customer investment priorities that create strategic openings for Circuit Check Quantify new market opportunities through analysis of TAM, competitive dynamics, segment profitability, and technology adjacencies; present data-supported recommendations to senior leadership Build and maintain industry relationships across the AI/ML ecosystem, including suppliers, contract manufacturers, analysts, and technology partners worldwide International Business Development Develop and execute customer engagement strategies in key AI/ML hubs, with emphasis on Silicon Valley and Taiwan Navigate international business environments including multi-stakeholder decision processes and cultural dynamics across Asia-Pacific Represent the company at international conferences, trade shows, and executive briefings as an authoritative voice on AI/ML infrastructure Sales Team Collaboration & Mentorship Mentor less experienced sales team members on complex deal strategy, multi-stakeholder navigation, and executive engagement Partner with assigned account team members who maintain day-to-day relationships, providing strategic direction while developing their capabilities Collaborate with Sales Leadership to build playbooks and best practices for pursuing large AI/ML infrastructure programs Education & Experience Bachelor's degree in Engineering (Electrical, Mechanical, or related) required; MBA or advanced technical degree preferred 10+ years of progressive experience in strategic account management, business development, or program leadership in semiconductor, electronic hardware, test & measurement, data center infrastructure, or related technology sectors Track record of winning and managing multi-million-dollar programs with complex, multi-stakeholder customer organizations Strongly preferred: executive-level relationships at hyperscale cloud providers; experience in the AI/ML hardware ecosystem (GPU test/validation, liquid cooling, power distribution, rack-scale integration, or related infrastructure) International business experience preferred, especially in the Taiwan semiconductor ecosystem and/or SE Asian manufacturing Knowledge, Skills & Abilities Strategic & Analytical Thinking Ability to see patterns across complex data, customer behaviors, and market signals - and translate insights into actionable strategies and business cases Rigorous analytical skills: financial models, program economics, pricing structures, and competitive intelligence that inform decision-making Thinks several moves ahead - anticipating customer needs, competitive responses, and market evolution Organizational & Execution Leadership Natural ability to orchestrate multiple moving parts - people, timelines, resources, priorities - across complex programs and matrixed organizations Skilled at configuring cross-functional teams for maximum effectiveness, with the program management discipline to track interdependencies and keep engagements on schedule and budget Presence & Influence Commanding executive presence with confidence to lead negotiations, challenge the status quo, and drive decisions in ambiguous situations Willingness to take charge, confront difficult issues directly, and provide clear direction when the path forward is uncertain Exceptional communication skills - compelling narratives, proposals, and presentations for technical and executive audiences Industry & Technical Acumen Deep understanding of the AI/ML data center ecosystem: GPU architectures, training/inference infrastructure, thermal management, power delivery, rack integration, and test/validation Credible in technical discussions with customer engineering teams while maintaining a business-outcome focus; proficient with CRM platforms (Salesforce preferred) Compensation & Performance Structure This role does not carry a traditional sales quota. Compensation includes a competitive base salary plus bonus objectives tied to: Winning new strategic AI/ML customers and capturing large new programs with existing accounts Growth in strategic account revenue and program pipeline value Program execution milestones and customer satisfaction metrics Location & Travel Requirements Open to remote candidates in the United States, with a preference for candidates in the San Francisco Bay Area, California Travel expected up to 50%, including customer visits throughout the Bay Area, across the US, and periodic international travel to Taiwan and SE Asia Must possess a valid passport and ability to obtain required travel visas Physical Requirements These physical requirements must be performed with or without accommodation: Time split between office/home office, customer sites, and travel Ability to sit for extended periods; bend, reach, stoop, and twist as required Heavy computer use; occasional exposure to manufacturing or lab environments Ability to lift and carry up to 25 lbs This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required of the employee. Duties, responsibilities, and activities may change at any time with or without notice. Pay and Benefits This job description reflects management's assignment of key responsibilities; it does not prescribe or restrict the tasks that may be assigned. Base pay is only one element of an employee's total compensation at Circuit Check. Employees (and their dependents in most plans) are covered by medical, dental, vision, basic life, short- and long-term disability and accidental death and dismemberment insurance. Employees are able to enroll in Circuit Check's 401k plan, in which the Company will match 50% of your contributions up to 6% with a maximum contribution. Paid time off includes vacation and sick time along with paid holidays. A summary of benefits can be provided by request via email to . Circuit Check, Inc. is proud to be an Equal Opportunity Employer. We do not discriminate based on identity, race, color, religion, national origin or ancestry, sex (including sexual identity), age, physical or mental disability, pregnancy, veteran or military status, genetic information, sexual orientation, marital status, or any other legally recognized protected basis under federal, state, or local law. Because Circuit Check is a federal contractor, we participate in the E-Verify program in certain locations, as required by law . click apply for full job details
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.
MANTECH seeks a motivated, career and customer-oriented Senior GEOINT Data Scientist to join our team in Springfield, VA! The Senior GEOINT Data Scientist will leverage their strong technical background and knowledge to support critical data environments, to include creating streamlined processes, evaluating unique datasets, and solving challenging intelligence issues. Responsibilities include but are not limited to: Working with large structured / unstructured data in a modeling and analytical environment to define and create streamline processes in the evaluation of unique datasets and solve challenging intelligence issues Leading and participating in the design of solutions and refinement of pre-existing processes Working with Program Managers and Product Owners to translate road map features into components/tasks, estimate timelines, identify resources, suggest solutions, and recognize possible risks Using exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data Researching and implementing optimization models, strategies, and methods to inform data management activities and analysis Applying big data analytic tools to large, diverse sets of data to deliver impactful insights and assessments Minimum Qualifications: High School Diploma/GED with 10+ years of progressively responsible experience in GEOINT analysis, intelligence analysis, or a related technical field Education/Training Substitutions: Associate's degree may substitute for 2 years of experience. Bachelor's degree may substitute for 3 years of experience. Master's degree may substitute for 2 years of experience. PhD may substitute for 3 years of experience. Professional certifications may substitute for up to 6 months of experience. Significant experience supporting IC operations, possessing expert level knowledge to manipulate and analyze structured/ unstructured data Demonstrated experience in data mining and developing/maintaining/manipulating databases Demonstrated experience in identifying potential systems enhancements, new capabilities, concept demonstrators, and capability business cases Demonstrated experience using GOTS data processing and analytics capabilities to modernize analytic methodologies Demonstrated experience in directing activities of highly skilled technical and analytical teams responsible for developing solutions to highly complex analytical/intelligence problems Experienced in conducting multi-INT and technology specific research to support mission operations Preferred Qualifications: Possess Master's degree in Data Science or related technical field with experience developing and working with Artificial Intelligence and Machine Learning (AI/ML) Demonstrated experience of advanced programming techniques, using one or more of the following: HTML 5/Javascript, ArcObjects, Python, Model Builder, Oracle, SQL, GIScience, Geospatial Analysis, Statistics, ArcGIS Desktop, ArcGIS Server, Arc SDE, ArcIMS Experience using .NET, Python, C++, and/or JAVA programming for web interface development and geodatabase development Experience building and maintaining databases of GEOINT, SIGINT, or OSINT data related to the area of interest needs Data Visualization Experience which may include Matrix Analytics, Network Analytics, Graphing Data that assist the analytical workforce in generating common operational pictures depicting fused intelligence and information to support informal assessments and finished products Clearance Required: An active TS/SCI with the ability to obtain & maintain a Polygraph Physical Requirements: Must be able to remain in a stationary position 50%. Needs to occasionally move about inside the office to access file cabinets, office machinery, etc. Frequently communicates with co-workers, management, and senior personnel, which may involve delivering presentations. Must be able to exchange accurate information in these situations.
08/04/2026
Full time
MANTECH seeks a motivated, career and customer-oriented Senior GEOINT Data Scientist to join our team in Springfield, VA! The Senior GEOINT Data Scientist will leverage their strong technical background and knowledge to support critical data environments, to include creating streamlined processes, evaluating unique datasets, and solving challenging intelligence issues. Responsibilities include but are not limited to: Working with large structured / unstructured data in a modeling and analytical environment to define and create streamline processes in the evaluation of unique datasets and solve challenging intelligence issues Leading and participating in the design of solutions and refinement of pre-existing processes Working with Program Managers and Product Owners to translate road map features into components/tasks, estimate timelines, identify resources, suggest solutions, and recognize possible risks Using exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data Researching and implementing optimization models, strategies, and methods to inform data management activities and analysis Applying big data analytic tools to large, diverse sets of data to deliver impactful insights and assessments Minimum Qualifications: High School Diploma/GED with 10+ years of progressively responsible experience in GEOINT analysis, intelligence analysis, or a related technical field Education/Training Substitutions: Associate's degree may substitute for 2 years of experience. Bachelor's degree may substitute for 3 years of experience. Master's degree may substitute for 2 years of experience. PhD may substitute for 3 years of experience. Professional certifications may substitute for up to 6 months of experience. Significant experience supporting IC operations, possessing expert level knowledge to manipulate and analyze structured/ unstructured data Demonstrated experience in data mining and developing/maintaining/manipulating databases Demonstrated experience in identifying potential systems enhancements, new capabilities, concept demonstrators, and capability business cases Demonstrated experience using GOTS data processing and analytics capabilities to modernize analytic methodologies Demonstrated experience in directing activities of highly skilled technical and analytical teams responsible for developing solutions to highly complex analytical/intelligence problems Experienced in conducting multi-INT and technology specific research to support mission operations Preferred Qualifications: Possess Master's degree in Data Science or related technical field with experience developing and working with Artificial Intelligence and Machine Learning (AI/ML) Demonstrated experience of advanced programming techniques, using one or more of the following: HTML 5/Javascript, ArcObjects, Python, Model Builder, Oracle, SQL, GIScience, Geospatial Analysis, Statistics, ArcGIS Desktop, ArcGIS Server, Arc SDE, ArcIMS Experience using .NET, Python, C++, and/or JAVA programming for web interface development and geodatabase development Experience building and maintaining databases of GEOINT, SIGINT, or OSINT data related to the area of interest needs Data Visualization Experience which may include Matrix Analytics, Network Analytics, Graphing Data that assist the analytical workforce in generating common operational pictures depicting fused intelligence and information to support informal assessments and finished products Clearance Required: An active TS/SCI with the ability to obtain & maintain a Polygraph Physical Requirements: Must be able to remain in a stationary position 50%. Needs to occasionally move about inside the office to access file cabinets, office machinery, etc. Frequently communicates with co-workers, management, and senior personnel, which may involve delivering presentations. Must be able to exchange accurate information in these situations.
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 The IS Consultant IV, Application Security position is a senior hands-on technical role responsible for leading complex application security assessments and advancing secure software development practices across the organization. The consultant will conduct secure code reviews, static and dynamic application security testing, open source component analysis, API and mobile application security assessments, threat modeling, security architecture reviews, vulnerability validation, and remediation guidance. The ideal candidate has advanced software development and application security experience using Java, Python, JavaScript, .NET, Swift, or similar technologies. The candidate should have practical experience with application security testing solutions, penetration testing tools such as Burp Suite or OWASP ZAP, and integrating security controls into CI/CD pipelines. This role requires the ability to independently lead complex assessments, define secure development standards and guardrails, evaluate third party applications, and influence architecture and engineering decisions. The consultant will collaborate with developers, architects, product owners, vendors, security leaders, and executive stakeholders to communicate technical risk clearly and provide actionable remediation recommendations. Experience with cloud native applications, APIs, mobile applications, AI enabled applications, DevSecOps automation, and healthcare or other regulated environments is preferred. Job Summary: In addition to responsibilities listed below, this position is responsible for reviewing application source code for potential security vulnerabilities by performing manual and automated security testing on applications in a running state (DAST); working with DevOps teams to integrate application security services; training DevOps personnel and developers to use application security tools; working one-on-one with developers to help them understand security vulnerabilities at hand and to identify/suggest remediation plans; and recommending application security training paths. This also includes responsibility for protecting applications in production by enrolling them for continuous assessment of existing and emerging threats, evaluating web application firewalls; tuning WAF rules; reviewing alerts; and identifying issues as appropriate. Essential Responsibilities: Completes work assignments and supports business-specific projects by applying expertise in subject area; supporting the development of work plans to meet business priorities and deadlines; ensuring team follows all procedures and policies; coordinating and assigning resources to accomplish priorities and deadlines; collaborating cross-functionally to make effective business decisions; solving complex problems; escalating high priority issues or risks, as appropriate; and recognizing and capitalizing on improvement opportunities. Practices self-development and promotes learning in others by proactively providing information, resources, advice, and expertise with coworkers and customers; building relationships with cross-functional stakeholders; influencing others through technical explanations and examples; adapting to competing demands and new responsibilities; listening and responding to, seeking, and addressing performance feedback; providing feedback to others and managers; creating and executing plans to capitalize on strengths and develop weaknesses; supporting team collaboration; and adapting to and learning from change, difficulties, and feedback. Effectively communicates investigative findings to non-technical audiences. Collaborates with technology risk teams and business stakeholders to respond to and remediate identified issues, and determine the best approach for improving security posture. Provides recommendations to management and business stakeholders on how to remediate issues identified through security testing processes. Identifies the impact of security test plans on upstream and downstream solution components. Supports information sharing and integration procedures across cyber security through the exchange of threat intelligence and cyber security vulnerability assessment data. Contributes to cyber security intellectual capital by making process or procedure improvements, conducting brown bag training sessions, and creating new training documents. Follows established processes to ensure KPI goals are obtained and performance metrics are tracked on an ongoing basis. Recommends business line or business technology team security process improvements which align with sustainable best practices, and the strategic and tactical goals of the business. Supports continuous process improvement by participating in the development, implementation, and maintenance of standardized security tools, templates, and processes across multiple business domains. Performs complex security test data analysis in support of security vulnerability assessment processes, including root cause analysis. Serves as an escalation point on issues, dependencies, and risks related to security testing. Executes the vulnerability assessment and penetration testing plan, methodologies, and standard processes for moderately to highly complex technology initiatives across multiple IT domains by analyzing business and technology requirements. Researches and stays abreast of industry trends, emerging threats, best practices, and cutting edge techniques to creatively discover and exploit vulnerabilities, and recommend security solutions for technology systems. Provides insight and consultation on the development of testing scope and approach, and collaborates with cross-functional IT and business stakeholders to review the overall testing approach. Validates security test scenarios across various SDLC phases (e.g., development, reproduction, production) for low- to moderately-complex projects. Generates scheduled reports (e.g., status updates, risk assessment reports, remediation reports) and provides regular security metrics to IT teams and management as appropriate. Minimum Qualifications: Minimum three (3) years software or application development experience. Minimum one (1) year experience in application security (e.g., source code analysis, dynamic analysis, etc.). Bachelors degree in Business Administration, Computer Science, Social Science, Mathematics, or related field and Minimum six (6) years experience in IT or a related field, including Minimum two (2) years in information security, network engineering, or application development. Additional equivalent work experience may be substituted for the degree requirement. Additional Requirements:
07/30/2026
Full time
Tech Summary The IS Consultant IV, Application Security position is a senior hands-on technical role responsible for leading complex application security assessments and advancing secure software development practices across the organization. The consultant will conduct secure code reviews, static and dynamic application security testing, open source component analysis, API and mobile application security assessments, threat modeling, security architecture reviews, vulnerability validation, and remediation guidance. The ideal candidate has advanced software development and application security experience using Java, Python, JavaScript, .NET, Swift, or similar technologies. The candidate should have practical experience with application security testing solutions, penetration testing tools such as Burp Suite or OWASP ZAP, and integrating security controls into CI/CD pipelines. This role requires the ability to independently lead complex assessments, define secure development standards and guardrails, evaluate third party applications, and influence architecture and engineering decisions. The consultant will collaborate with developers, architects, product owners, vendors, security leaders, and executive stakeholders to communicate technical risk clearly and provide actionable remediation recommendations. Experience with cloud native applications, APIs, mobile applications, AI enabled applications, DevSecOps automation, and healthcare or other regulated environments is preferred. Job Summary: In addition to responsibilities listed below, this position is responsible for reviewing application source code for potential security vulnerabilities by performing manual and automated security testing on applications in a running state (DAST); working with DevOps teams to integrate application security services; training DevOps personnel and developers to use application security tools; working one-on-one with developers to help them understand security vulnerabilities at hand and to identify/suggest remediation plans; and recommending application security training paths. This also includes responsibility for protecting applications in production by enrolling them for continuous assessment of existing and emerging threats, evaluating web application firewalls; tuning WAF rules; reviewing alerts; and identifying issues as appropriate. Essential Responsibilities: Completes work assignments and supports business-specific projects by applying expertise in subject area; supporting the development of work plans to meet business priorities and deadlines; ensuring team follows all procedures and policies; coordinating and assigning resources to accomplish priorities and deadlines; collaborating cross-functionally to make effective business decisions; solving complex problems; escalating high priority issues or risks, as appropriate; and recognizing and capitalizing on improvement opportunities. Practices self-development and promotes learning in others by proactively providing information, resources, advice, and expertise with coworkers and customers; building relationships with cross-functional stakeholders; influencing others through technical explanations and examples; adapting to competing demands and new responsibilities; listening and responding to, seeking, and addressing performance feedback; providing feedback to others and managers; creating and executing plans to capitalize on strengths and develop weaknesses; supporting team collaboration; and adapting to and learning from change, difficulties, and feedback. Effectively communicates investigative findings to non-technical audiences. Collaborates with technology risk teams and business stakeholders to respond to and remediate identified issues, and determine the best approach for improving security posture. Provides recommendations to management and business stakeholders on how to remediate issues identified through security testing processes. Identifies the impact of security test plans on upstream and downstream solution components. Supports information sharing and integration procedures across cyber security through the exchange of threat intelligence and cyber security vulnerability assessment data. Contributes to cyber security intellectual capital by making process or procedure improvements, conducting brown bag training sessions, and creating new training documents. Follows established processes to ensure KPI goals are obtained and performance metrics are tracked on an ongoing basis. Recommends business line or business technology team security process improvements which align with sustainable best practices, and the strategic and tactical goals of the business. Supports continuous process improvement by participating in the development, implementation, and maintenance of standardized security tools, templates, and processes across multiple business domains. Performs complex security test data analysis in support of security vulnerability assessment processes, including root cause analysis. Serves as an escalation point on issues, dependencies, and risks related to security testing. Executes the vulnerability assessment and penetration testing plan, methodologies, and standard processes for moderately to highly complex technology initiatives across multiple IT domains by analyzing business and technology requirements. Researches and stays abreast of industry trends, emerging threats, best practices, and cutting edge techniques to creatively discover and exploit vulnerabilities, and recommend security solutions for technology systems. Provides insight and consultation on the development of testing scope and approach, and collaborates with cross-functional IT and business stakeholders to review the overall testing approach. Validates security test scenarios across various SDLC phases (e.g., development, reproduction, production) for low- to moderately-complex projects. Generates scheduled reports (e.g., status updates, risk assessment reports, remediation reports) and provides regular security metrics to IT teams and management as appropriate. Minimum Qualifications: Minimum three (3) years software or application development experience. Minimum one (1) year experience in application security (e.g., source code analysis, dynamic analysis, etc.). Bachelors degree in Business Administration, Computer Science, Social Science, Mathematics, or related field and Minimum six (6) years experience in IT or a related field, including Minimum two (2) years in information security, network engineering, or application development. Additional equivalent work experience may be substituted for the degree requirement. Additional Requirements:
