21 jobs found

Preferred Profile A seasoned Mainframe Test Architect and Quality Leader with deep experience in migration and modernization programs, capable of building the testing strategy, tooling ecosystem, automation framework, and governance model necessary to successfully deliver a complex enterprise migration from legacy Mainframe environments to z/OS while minimizing business and operational risk. Position Summary We are seeking an experienced Test Architect to lead the end-to-end testing strategy, planning, governance, tooling, and quality assurance approach for a large-scale z/VSE to z/OS migration program. This role will be responsible for defining the overall testing framework, establishing risk-based testing methodologies, driving quality governance, and ensuring comprehensive validation of applications, infrastructure, data, security, and operational processes throughout the migration lifecycle. The ideal candidate will possess deep Mainframe testing and modernization expertise and have experience leading testing efforts for Mainframe migrations, platform transformations, or large-scale legacy modernization initiatives. A key responsibility of this role is establishing a risk-based testing strategy, ensuring testing effort is aligned to the scope, complexity, and business impact of migration-related changes rather than applying uniform testing across all components. Additionally, this role will be responsible for defining and implementing the testing toolchain and automation strategy required to support the migration program, including test management, automation, data reconciliation, regression testing, defect management, and AI-assisted testing capabilities. Key Responsibilities Test Strategy & Governance Define and own the overall migration testing strategy, framework, roadmap, and governance model. Establish testing standards, quality gates, entry/exit criteria, and release readiness processes. Develop a risk-based testing methodology aligned to migration waves and deployment milestones. Establish traceability between migration changes, risks, business requirements, and test coverage. Provide executive reporting on testing progress, quality metrics, risks, and release readiness. Risk-Based Testing & Change Impact Assessment Lead application, infrastructure, and operational impact assessments to understand migration-related changes. Develop a risk-ranking framework to classify components based on:Code modifications JCL conversion impacts Platform configuration changes Data migration impacts CICS transaction changes Interface dependencies Security changes Operational and scheduler impacts Business criticality Define testing depth and coverage based on migration risk and business impact. Optimize testing effort by focusing on high-risk and high-business-value components. Maintain a Migration Testing Risk Register and Quality Heat Map. Identify migration-specific risks and ensure mitigation plans are incorporated into testing activities. Test Tooling, Automation & AI Strategy Define the overall testing tool architecture and strategy for the migration program. Evaluate, select, and implement testing tools supporting:Test management Defect management Test automation Data reconciliation Batch validation Regression testing Performance testing Reporting and dashboards Establish automated validation approaches for batch jobs, file comparisons, data reconciliation, and migration verification. Design reusable automation frameworks and testing accelerators. Identify opportunities to leverage AI-enabled testing capabilities for:Test case generation Impact analysis Regression optimization Defect clustering and analysis Test productivity improvement Establish testing KPIs and quality metrics to measure effectiveness and automation adoption. Test Planning & Design Develop comprehensive testing plans covering:System Testing System Integration Testing (SIT) End-to-End Business Process Testing Regression Testing Data Validation & Reconciliation Testing Performance & Volume Testing User Acceptance Testing (UAT) Operational Readiness Testing Cutover & Rollback Validation Testing Define test environments, test data strategy, and environment governance. Ensure test coverage aligns with migration risk profiles and business priorities. Mainframe & Migration Validation Define testing coverage for:COBOL applications Assembler programs Easytrieve applications CICS transactions JCL conversion and batch processing VSAM files DL1-dependent applications and data structures File transfers and interfaces Security configurations and access controls Enterprise scheduling platforms Infrastructure and operational procedures Validate functional equivalence and operational readiness of workloads migrated to z/OS. Ensure reconciliation of data, interfaces, and business processes before production deployment. Validate production support, monitoring, scheduling, and recovery procedures. Federated Test Leadership Coordinate testing activities across:Mainframe Teams Application Teams Infrastructure Teams Security Teams Operations Teams Business SMEs Establish testing standards, reusable assets, and governance across workstreams. Lead defect triage, prioritization, and remediation activities. Drive issue resolution and dependency management across teams. Mentor test leads and testing workstreams throughout the program. Cutover Readiness & Deployment Validation Define mock migration, deployment rehearsal, and cutover validation strategies. Validate production deployment procedures and rollback capabilities. Ensure critical business processes successfully execute during migration rehearsals. Assess operational readiness and support preparedness. Provide Go/No-Go recommendations for migration releases. Required Qualifications Mainframe & Migration Experience 10+ years of experience in Test Architecture, Test Management, or Quality Engineering leadership roles. Strong knowledge of Mainframe application development, testing, and migration methodologies. Hands-on experience with:z/OS COBOL Assembler Easytrieve CICS JCL VSAM DL1-related environments RACF, ACF2, or Top Secret Batch processing frameworks Enterprise scheduling platforms Experience supporting Mainframe modernization, migration, platform transformation, or large-scale legacy remediation programs. Experience validating high-volume business-critical workloads and operational processes. Prior z/VSE migration experience is preferred but not required. Testing Tools & Automation Experience Experience selecting and implementing enterprise-scale testing toolsets. Experience with test management, defect management, reporting, automation, and quality governance tools. Proven experience implementing automated regression, reconciliation, and data validation frameworks. Familiarity with AI-assisted testing platforms and productivity tools. Experience integrating testing activities into DevOps and CI/CD processes where applicable. Modern Mainframe Engineering Experience Experience with modern Mainframe development and testing environments such as:IBM Developer for z/OS (IDz) VS Code-based Mainframe tooling Git-based source control Enterprise DevOps toolchains Understanding of modern software engineering practices applied to Mainframe environments. Risk-Based Testing Expertise Proven experience implementing risk-based testing methodologies for large-scale transformation programs. Strong ability to conduct migration impact assessments and translate findings into targeted testing strategies. Experience prioritizing test coverage based on technical, operational, business, and compliance risks. Demonstrated ability to balance quality, coverage, risk, and program timelines. Leadership & Communication Experience leading large, cross-functional testing organizations. Strong stakeholder management skills across business and technology teams. Exceptional executive communication and governance reporting capabilities. Ability to influence senior leaders, architects, and delivery teams in complex transformation programs. Key Deliverables Enterprise Test Strategy Risk-Based Testing Framework Migration Test Plan Test Coverage Matrix Testing Toolchain Strategy & Architecture Automation & Regression Testing Strategy AI-Enabled Testing Adoption Roadmap Test Environment & Test Data Strategy Impact Assessment & Risk Heat Map Data Reconciliation & Validation Framework SIT & End-to-End Test Plans Defect Management Process Cutover Rehearsal Plan Operational Readiness Assessment Go/No-Go Readiness Assessments Executive Quality Dashboards

Job Description Job Description We are looking for a senior ML infrastructure engineer to build and evolve the systems that support model training, deployment, and production usage. This role sits at the intersection of software engineering, infrastructure, ML workflows, and developer experience. The work focuses on production-quality ML systems: reliability, scalability, observability, and usability for the team. You will work on training infrastructure, deployment workflows, model serving, platform tooling, automation, and production reliability. Training deployment is a core focus, and experience with inference deployment is a strong plus. We care about engineering judgment, technical depth, communication, and the ability to turn messy ML workflows into stable platform capabilities. What You Will Own Design, build, and evolve infrastructure for ML training workflows, training deployment, experiment execution, and production handoff. Build and maintain deployment paths for models, jobs, services, and supporting infrastructure across development and production environments. Improve reliability, scalability, observability, and developer experience for ML workflows and platform tools. Define interfaces, automation, metadata, artifacts, configuration, environment management, and lifecycle boundaries for ML systems. Collaborate with research, product, data, and engineering partners to translate incomplete ML workflow needs into maintainable systems. Support production usage by building clear operational tooling, debugging paths, and safe rollout mechanisms. What We Look For Strong software engineering and infrastructure fundamentals, with experience owning production or near-production systems. Practical experience with PyTorch and ML training workflows, including job orchestration, compute environments, artifact management, and deployment automation. Solid understanding of heterogeneous computing and high-performance computing, especially for ML training or serving workloads. Good understanding of model lifecycle concerns: data, configs, checkpoints, artifacts, reproducibility, rollout, rollback, and observability. Ability to build reliable platform abstractions without hiding the important details ML practitioners need to control. Clear technical and product sense: you can prioritize platform work that unlocks real training or deployment velocity. High standards for engineering quality, including tests, documentation, debugging tools, and maintainable system design. Tech Stack You May Work With Python PyTorch Heterogeneous computing and high-performance computing ML training pipelines, job orchestration, compute scheduling, containers, and deployment automation Model artifacts, metadata, storage, experiment tracking, and configuration systems Model serving, inference deployment, APIs, queues, and observability tools Docker, CI/CD, cloud infrastructure, GPUs, and internal platform tooling Bonus Points Experience building training deployment systems, model release workflows, or ML platform tooling for research and production teams. Experience with inference deployment, model serving, online/offline evaluation, performance tuning, or rollout safety. Experience with distributed training, GPU infrastructure, workload scheduling, artifact/version management, or reproducibility tooling. Understanding of CUDA, GPU architecture, or low-level performance optimization. Experience with open-source inference and serving frameworks such as vLLM, TensorRT, Triton, or similar systems. Experience migrating ad hoc notebooks, scripts, or manual ML processes into reliable platform workflows. This Role May Not Be a Fit If You mainly want to train models personally and do not enjoy building infrastructure for others to use. You are comfortable with manual ML workflows and do not care about reproducibility, deployment, or operational quality. You prefer narrow implementation tasks and do not want to reason about system boundaries, platform UX, or long-term maintenance. You over-abstract ML workflows without understanding where researchers and engineers need control and visibility. Why This Role Matters ML teams move faster when training, deployment, and production usage are supported by reliable infrastructure instead of scattered scripts and manual processes. This role will directly shape how models move from experimentation to production, how safely they are deployed, and how efficiently the team can iterate. For the right person, it is a high-ownership platform role with deep impact on both engineering quality and ML velocity. What We Would Like to See When You Apply ML infrastructure, training platforms, deployment systems, or model serving systems you have owned. Examples of how you improved training reliability, deployment velocity, reproducibility, observability, or operational safety. Cases where you turned messy ML workflows into maintainable tools, services, or platform abstractions. Examples that show your technical judgment, communication, and ability to work across research and engineering needs.

Job Description Job Description About the Role Teserac is building neuron , a unified AI-native platform for data center observability, intelligence, and workflow automation. neuron processes real-time telemetry from thousands of sensors, meters, and control systems across heterogeneous environments - giving infrastructure owners the visibility to monitor, analyze, automate, and proactively manage power operations with full situational awareness. An embedded AI teammate serves as every operator's always-on co-pilot: detecting anomalies, correlating events, and surfacing recommendations 24/7. We are seeking an AI/ML Engineer who is excited to build intelligent systems at the intersection of applied AI and critical infrastructure. You will work across the full AI development lifecycle - from data pipelines and model integration to agentic orchestration, evaluation, and production support - collaborating closely with a small, fast-moving engineering team. This is not a research-only role, but research thinking matters here. You will be expected to read papers, stay ahead of the field, and bring ideas to the table - then build them into production systems. Who We Are Looking For We care more about how you think than how many years are on your resume. This role is open to both junior and senior candidates. What matters is: You are genuinely excited about AI and infrastructure - not just one of them You learn fast, go deep, and can hold your own in a technical debate You have the engineering fundamentals to ship reliable systems You are proactive, curious, and comfortable with a steep learning curve You want to work on something technically hard that actually matters in the physical world If you are early in your career but have strong fundamentals, a track record of self-directed learning, and a portfolio that shows you build things - we want to hear from you. What You Will Work On Multi-agent orchestration and LLM-driven triage workflows Time-series modeling for anomaly detection, failure prediction, and health forecasting on multivariate telemetry Retrieval-augmented knowledge systems for operations teams Data and ML pipelines - ingestion, ETL, and dataset construction Fine-tuning and post-training of language models for operational use cases AI observability, evaluation frameworks, and production performance benchmarking Responsibilities Design, develop, and maintain AI-powered applications and automation workflows Integrate and optimize LLM APIs for production use cases Build and refine retrieval and knowledge-augmentation pipelines Develop evaluation frameworks to benchmark AI system performance Implement monitoring, tracing, and debugging capabilities for AI systems Read and synthesize relevant research; bring ideas forward and debate them with the team Contribute to AI architecture decisions and production hardening Stay current with the rapidly evolving AI/ML landscape Requirements Required Degree in Computer Science, Machine Learning, Mathematics, or a related field - or equivalent demonstrated experience Strong proficiency in Python Solid software engineering fundamentals: testing, version control, CI/CD Experience working with LLM APIs in applied contexts Familiarity with agentic system concepts - tool/function-calling, agent frameworks Daily use of AI-assisted coding tools (Cursor, Copilot, Claude Code, etc.) Ability to read ML research papers and translate ideas into practical experiments Strong analytical thinking and clear communication - you can argue a position and update it when wrong Preferred Professional AI/ML engineering experience (any level) Experience building agentic systems using frameworks such as LangGraph or LangChain; MCP a plus Time-series modeling - forecasting and anomaly/failure prediction on multivariate data Experience fine-tuning or post-training language models PyTorch and/or model serving frameworks (e.g., vLLM) Experience building data and ML pipelines - ingestion, ETL, dataset construction Familiarity with cloud ML platforms, particularly GCP (Vertex AI) LLM evaluation and benchmarking: harness design and eval loop development Domain experience with data center or industrial telemetry, BMS/OT protocols (Niagara, BACnet/Modbus) Background in DevOps, distributed systems, or observability tooling Benefits Health Care Plan (Medical, Dental & Vision) Paid Time Off (Vacation, Sick & Public Holidays) Free Food & Snacks Stock Option Plan 401(k)

Job Description Job Description Zilliz is a fast-growing startup developing the industry's leading vector database for enterprise-grade AI. Founded by the engineers behind Milvus, the world's most popular open-source vector database, the company builds next-generation database technologies to help organizations quickly create AI applications. On a mission to democratize AI, Zilliz is committed to simplifying data management for AI applications and making vector databases accessible to every organization. We're entering our next phase of 10x growth; more customers, larger datasets, and far higher expectations for reliability. You'll join a small, fast-moving Cloud Platform team that operates large-scale, multi-cloud, distributed database systems in production. This is a high-ownership role for engineers who want to move fast, build automation instead of toil, and take real responsibility for production stability. What you will do: Own the reliability, availability, and production stability of Zilliz Cloud as we scale through the next stage of growth Debug complex production issues across Kubernetes, cloud infrastructure, networking, storage, and distributed database systems Build automation and diagnostic tooling; log analysis, alert correlation, incident investigation, runbook automation, and remediation workflows so problems get solved once, not repeatedly Turn recurring incidents into reusable tools, automation, documentation, and product improvements Improve observability across latency, availability, throughput, and resource efficiency Partner with database and infrastructure engineers to make Zilliz Cloud more reliable, scalable, and automated What we are looking for: 3+ years building or operating production cloud systems, infrastructure platforms, database systems, or large-scale online services Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience Strong hands-on experience with Kubernetes, Docker, and at least one major cloud platform (AWS, GCP, or Azure) Solid understanding of distributed systems; availability, scalability, performance, failure recovery, and operational tradeoffs Experience with distributed databases, storage systems, search systems, or large-scale online systems is a strong plus Experience operating highly multi-tenant systems or large infrastructure fleets; thousands of nodes, clusters, tenants, or customer deployments is especially valuable Familiarity with modern cloud operations tooling such as Terraform, Helm, Argo CD, Prometheus, Grafana, and CI/CD systems Strong bias for action, and the drive to thrive in a fast-paced, rapidly scaling environment How we operate: High ownership: You own production reliability end-to-end. The whole system, not a slice of it. High autonomy, high trust, minimal process. Fast and focused: We ship often and keep a high bar. This team suits engineers who want velocity and a steep growth curve over red tape. Globally distributed: We work closely with our core engineering teams across APAC. Occasional early morning or evening syncs in exchange for an on-call setup designed around timezone coverage, not overnight pages. Zilliz is an Equal Opportunity Employer and welcomes people from all backgrounds, experiences, abilities, and perspectives. All qualified applicants will receive consideration for employment regardless of race, color, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, or length of time spent unemployed. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Job Description RETHINK MANUFACTURING The only way to ignite change is to build the best team. At Bright Machines , we're innovators and experts in our craft who have joined together to manufacture the AI and data center infrastructure at the edge. We believe unifying software, intelligent automation, and data is the answer to delivering quality and flexibility at scale. We deliver products to meet the demands of today while continuously investing in our Bright Factory model to take advantage of what comes next. Working with us means you'll have the opportunity to make lasting, impactful changes for our company and our customers. If you're ready to apply your exceptional skills to a brighter way of manufacturing AI infrastructure, we'd love to speak with you. ABOUT THE ROLE As a senior Robot Perception Engineer on the Smart Robotics team at Bright Machines, you will be a hands-on senior contributor responsible for productizing visual inspection solutions for our automation platform. You will own the full pipeline-from algorithm development to production deployment-turning prototype inspection capabilities into reliable, high-throughput features that operate at scale across our automation lines. In this role, you will develop and optimize computer vision and deep learning models for defect detection, classification, and visual validation. You will collaborate closely with cross-functional teams, including Mechanical Engineering and Manufacturing Operations, to design end-to-end inspection solutions that deliver consistent, accurate results under real-world factory conditions. Additionally, you will have the opportunity to shape the inspection product roadmap and drive the adoption of cutting-edge machine learning techniques in an industrial setting. WHAT YOU WILL BE DOING Develop and optimize visual inspection algorithms for defect detection, anomaly detection, classification, and quality validation using deep learning Optimize model inference for GPU deployment, leveraging CUDA, TensorRT, and related acceleration frameworks Collaborate with Mechanical engineers to design illumination setups that maximize inspection accuracy and robustness Build and maintain data pipelines for model training, evaluation, and continuous improvement Partner with platform team to establish MLOps practices for model versioning, experiment tracking, automated retraining, and production model monitoring Harden inspection solutions for production reliability, including monitoring, alerting, and graceful degradation Work with service engineering and field teams to deploy inspection solutions and support customer rollouts Define metrics and benchmarks to measure inspection accuracy, throughput, and reliability WHAT YOU WILL BRING MS or PhD in Computer Science, Electrical Engineering, or a related field, or the equivalent in experience with evidence of exceptional ability. 5+ years of relevant experience in computer vision and/or machine learning Strong programming skills in Python Deep experience with PyTorch for model development and training Experience optimizing ML models for GPU inference in production environments Track record of shipping ML/CV models from prototype to production Experience with image acquisition, camera systems, and sensor integration IT WOULD BE GREAT IF YOU HAD Knowledge of lighting and optics for machine vision (diffuse/directional illumination, lens and filters) Experience with industrial camera systems and standards (GigE Vision, GenICam, CoaXPress) C/C++ experience for performance-critical components Experience with MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) Experience with data annotation, labeling workflows, and active learning strategies Experience with ROS2 Understanding of manufacturing processes and quality control methodologies Publications or patents in computer vision, deep learning, or related fields BE EMPOWERED TO CHANGE AN INDUSTRY Bright Machines is a next-generation, AI-enabled manufacturer focused on data center infrastructure production. Bright Machines uses its proprietary AI-based robotics and software to assemble AI infrastructure hardware products (i.e., data center servers) for hyperscalers, neoclouds, and leading Original Equipment Manufacturers (OEMs) to reduce their time to revenue. With its Bright Factory model, Bright Machines builds higher quality data center infrastructure at scale, addresses increasing market demands for computing power due to the surge of AI, and answers the call to the U.S. national mandate to reshore manufacturing. Bright Machines is headquartered in San Francisco, California, with an integration center in Guadalajara, Mexico. The company has been recognized as one of Forbes' AI 50, awarded "Best AI-based Solution for Manufacturing" by AI Breakthrough, named a "Technology Pioneer" by the World Economic Forum, and highlighted by several other leading technology and innovation organizations.

Job Description Job Description Crusoe is on a mission to accelerate the abundance of energy and intelligence . As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack - from electrons to tokens - to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that - with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved - people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About the Role: We are seeking a highly skilled, hands-on Senior level performance engineer who thrives on deep technical challenges. The ideal candidate possesses a mastery of Linux kernel systems and low-level optimization, with a collaborative mindset to drive cross-functional projects. This is a full-time position where you will roll up your sleeves to perform direct performance benchmarking and system tuning, making a tangible impact on Crusoe's global compute operations. What You'll Be Working On: System Performance Benchmarking : Design and execute rigorous benchmarks to analyze system behavior, identifying bottlenecks and opportunities for performance enhancement. Kernel Optimization : Develop and implement low-level optimizations within the Linux kernel to maximize efficiency and system throughput. Hands-on Development : Write and maintain high-performance code using Go, C, C++, or Rust to drive infrastructure improvements. Data Plane Tuning : Focus on data plane performance, ensuring our cloud architecture meets the high-speed requirements of modern AI workloads. Cross-Functional Collaboration : Partner closely with Software Infrastructure, Product, and other engineering teams to align performance initiatives with broader organizational goals. Technical Problem-Solving : Actively troubleshoot complex system issues, applying an analytical approach to ensure reliability and scalability. Strategic Knowledge Sharing : Contribute to team documentation and best practices, fostering a culture of technical excellence and continuous improvement. What You'll Bring to the Team: Linux Kernel Mastery : Deep expertise in Linux system internals and kernel-level programming is essential for this role. Programming Proficiency : Expert-level skills in Go, C, and C++ (Rust is also a strong asset). Systems Performance Mindset : A proven track record of hands-on performance tuning, benchmarking, and optimization in complex environments. Educational Foundation : A bachelor's degree in Computer Science, Engineering, or a related field, or equivalent professional experience. Collaborative Spirit : Ability to work effectively within cross-functional teams, communicating complex technical concepts clearly to stakeholders. AI Ecosystem Familiarity : Experience or exposure to the Artificial Intelligence/Cloud ecosystem and standard industry tooling. Bonus Points: Hands-on experience with Rust development. Prior experience working in high-scale cloud or infrastructure engineering environments Deep familiarity with performance-critical infrastructure components beyond the kernel layer. Experience with specific low-level performance analysis and tracing tools. Benefits: Competitive compensation and equity packages Restricted Stock Units Paid time off, paid holidays & leave of absence programs Comprehensive health, dental & vision insurance Employer contributions to HSA account Paid parental leave Paid life insurance, short-term and long-term disability Professional development & tuition reimbursement Mental health & wellness support Commuter benefits (parking & transit) Cell phone stipend 401(k) Retirement plan with company match up to 4% of salary Volunteer time off Global travel insurance & emergency assistance Daily meals allowance Additional perks & programs specific to location Compensation Range Compensation will be paid in the range of up to $ 170,000 - $205,000. + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

Job Description Job Description Job Description Senior Engineer, Internal Tools, Artificial Intelligence (AI) Required, Work From Home The Senior AI Engineer is the engineering backbone of the internal tools team. Building and maintaining the platforms that every team in the company relies on. Your work directly increases organizational efficiency and enables teams to move faster. The Senior AI Engineer will own systems end-to-end, from scoping and architecture through production deployment and iteration, connecting multiple business systems into a seamless, reliable internal ecosystem. This position is 100% Remote. Senior Engineer Responsibilities: Build & Ship: - Design, build, and maintain internal platforms and tools that serve People, Finance, Ops, Sales, and Engineering teams. - Own features, end-to-end requirements, architecture, implementation, testing, deployment, and monitoring. - Write clean, well-tested, production-grade code. You hold yourself to the same bar as customer-facing products. Architecture & Integration: - Build API-first integrations across the internal ecosystem connecting HRIS, CRM, finance platforms, knowledge management, and developer tools into a coherent stack. - Design for reliability, performance, and scale what you build today must hold as the company grows 5-10x. - Eliminate data silos. Build clean data pipelines that maintain a single source of truth across systems. - Own your services in production: monitoring, alerting, incident response, and post-mortems. AI & Automation: - Build AI/LLM-powered features into internal workflows, automating approvals, knowledge retrieval, reporting, content generation, and operational processes. - Move fast from prototype to production. You know the difference between a demo and a system that works at scale. - Stay current on emerging AI capabilities and proactively identify where they unlock step-change improvements in internal productivity. Collaboration & Influence: - Work directly with business stakeholders to understand pain points and translate them into technical solutions. You don't wait for a spec you help shape it. - Pair with and mentor junior engineers. Raise the technical bar through code reviews, design reviews, and leading by example. - Influence technical direction: propose architectural improvements, challenge assumptions, and drive best practices across the team. Qualifications Senior Engineer Qualifications: - 5+ years of professional software engineering experience, with meaningful time spent building internal tools, platforms, or business systems. - Artificial Intelligence (AI) experience required. - Strong full-stack or backend engineering skills. Proficient in at least one of: Python, Go, TypeScript/Node.js, or Java. - Solid understanding of Cloud Infrastructure (GCP/AWS/Azure), Containerization (Docker/Kubernetes), CI/CD Pipelines, and modern DevOps practices. - Hands-on experience building and maintaining API integrations between third-party SaaS platforms (e.g., Workday, Salesforce, Slack, NetSuite). - Strong data fundamentals: relational databases, data modelling, ETL/ELT pipelines, and working knowledge of SQL. - Comfort with ambiguity. You can take a vague business problem, break it down, and deliver a working solution without heavy handholding. - Clear communicator who can explain technical tradeoffs to non-technical stakeholders. - Experience with workflow orchestration tools (Temporal, Airflow, Prefect) or integration platforms (Workato, Tray.io, MuleSoft) is a plus. - Frontend experience with React, Next.js, or equivalent modern frameworks is a plus. - Familiarity with HRIS, ERP, or people systems data models and processes is a plus. - Experience at a high-growth or AI-native company is a plus. - Contributions to developer experience tooling, CLIs, or internal SDKs is a plus. - Experience building or integrating AI/LLM-powered features not just experimenting, but shipping to real users is a plus. Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc. Looking to hire a Senior Engineer in San Francisco, CA or in other cities? Our IT recruiting agencies and staffing companies can help. We help companies that are looking to hire Senior Engineers for jobs in San Francisco, California and in other cities too. Please contact our IT recruiting agencies and IT staffing companies today! Additional Information Please check out all of our jobs at .

Job Description Job Description Hadrian - Manufacturing the Future Hadrian is building autonomous factories that help aerospace and defense companies manufacture rockets, satellites, jets, and ships up to 10x faster and up to 2x cheaper. By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how America produces its most critical parts. We're accelerating our mission with the launch of Factory 3 in Mesa, Arizona, a 290,000-square-foot facility creating 350 new jobs. We are expanding rapidly to support thousands of future hires, launching Hadrian Maritime to expand into naval production, and introducing a Factory-as-a-Service model that delivers complete systems instead of individual parts. Hadrian is backed by leading investors including T. Rowe Price, Lux Capital, Founders Fund, and Andreessen Horowitz, our fast-growing team is united around reindustrializing American manufacturing for the 21st century and beyond. The Role Every engineer at Hadrian ships software. The speed and quality of that work depends directly on the tools, pipelines, and workflows underneath it. The Builder Tools team owns that foundation. As a Software Engineer on the Builder Tools team, you will build and maintain the CI/CD infrastructure, internal tooling, and AI-assisted development workflows that every engineering team at Hadrian depends on. Your users are Hadrian's engineers, and your job is to make them faster. That means owning shared pipeline libraries, reducing friction in the SDLC, making internal systems accessible to AI coding agents, and automating the work that slows teams down. This is a high-leverage role. The systems you build touch every engineer at Hadrian, and the improvements you ship show up immediately in how fast the company moves. What You'll Do Build and maintain CI/CD pipeline libraries that abstract build, release, and deployment events for use across multiple engineering teams Design and build internal tools, APIs, and CLI utilities that reduce developer friction and automate recurring engineering tasks - dependency upgrades, credential rotation, routine maintenance Help make Hadrian's internal systems API-ready for AI coding agents; build harness tooling, context systems, and feedback loops that improve the quality of AI-generated contributions in our codebase Instrument and monitor developer productivity systems; surface bottlenecks and measure the impact of tooling improvements through clear metrics Partner with application development teams to identify needs, implement CI/CD best practices, and drive adoption of new tooling across the org Join the on-call rotation to support systems and services during production incidents; contribute to root cause analyses and postmortems Participate in code reviews and author technical proposals that raise the engineering bar for the Builder Tools team What We're Looking For 5-8 years of software engineering experience, with at least 2-3 years focused on CI/CD, developer tooling, or build infrastructure Hands-on experience building and maintaining complex CI/CD pipelines and build infrastructure - pipeline-as-code, artifact management, multi-environment deployments Strong programming fundamentals in Go, Python, TypeScript, or similar; track record of writing clean, maintainable, well-tested code Experience with Docker and container orchestration (Kubernetes or similar) Solid understanding of source control concepts and practical Git experience Proven ability to troubleshoot complex systems and resolve issues efficiently A developer empathy mindset: you build tools that are easy to adopt, well-documented, and reduce toil rather than create it Bachelor's degree in Computer Science or related field, or equivalent experience What Will Set You Apart Genuine curiosity and hands-on experience with AI coding tools and agents - Copilot, Cursor, Claude Code, or similar - and opinions about what makes them work well in a real codebase Experience building API-ready interfaces or harness tooling for AI coding agents Prior work on developer experience or engineering productivity programs Familiarity with GitOps principles and workflows Experience with static analysis, automated PR pipelines, or code review tooling Background in fast-paced or scaling startup environments Growth & Trajectory The Builder Tools team is being built from the ground up, and this is one of the foundational IC roles on it. As the team grows and the function matures, there are opportunities to specialize in AI-assisted developer workflows, CI/CD platform ownership, or SDK/API development - and to grow into a senior IC or tech lead role as the org scales. Compensation For this role, the target salary range is $120,000- $250,000 (actual range may vary based on experience). This is the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee's pay position within the salary range will be based on several factors, including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. Benefits for Full-time Employees Medical, dental, vision, and life insurance plans for employees 401k Relocation support may be provided for certain situations, based on business need. Flexible vacation policy Equity ITAR Requirements To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here. Hadrian Is An Equal Opportunity Employer It is the Company's policy to provide equal employment opportunity for all applicants and employees. The Company does not unlawfully discriminate on the basis of race inclusive of traits historically associated with race (including, but not limited to, hair texture and protective hairstyles, such as braids, locks and twists), color, religion, sex (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, transgender status, national origin (including, in California, possession of a drivers license), ancestry, citizenship, age, physical or mental disability, height or weight, medical condition, family care status, military or veteran status, marital status, domestic partner status, sexual orientation, genetic information, exercise of reproductive rights, any other basis protected by local, state, or federal laws, or any combination of the above characteristics. When necessary, the Company also makes reasonable accommodations for disabled candidates and employees, including for candidates or employees who are disabled by pregnancy, childbirth, or related medical conditions. Compensation Range: $164.5K - $233K

Job Description Job Description About Us: We are building a robust, scalable trading platform to serve high-traffic, latency-sensitive applications. Our infrastructure leverages state-of-the-art technologies to support real-time trading while providing unparalleled reliability and performance. Join us to shape the future of our platform and engineering culture. Job Summary: We are looking for a Senior DevOps & Platform Engineer to lead the design, implementation, and management of our AWS-centric infrastructure. You will play a pivotal role in maximizing the velocity of our product engineering team, ensuring platform scalability, reliability, and security. This is a high-impact role, combining elements of DevOps, Platform Engineering, and Site Reliability Engineering (SRE). You will champion best practices, shape the engineering culture, and ensure our platform is robust, efficient, and ready for the future. Key Responsibilities: Platform Engineering Infrastructure Design: Architect and implement scalable infrastructure to support the deployment and management of our trading platform. Developer Tooling: Build and maintain internal tools to streamline developer workflows, including advanced CI/CD pipelines. Infrastructure as Code (IaC): Champion IaC practices using Terraform, CloudFormation, or Pulumi. Core Services Management: Manage and optimize platform-critical services such as: NATS Cluster RabbitMQ AWS RDS PostgreSQL Redis Cluster DevOps Automation and CI/CD: Automate and optimize deployment processes to ensure seamless continuous integration and delivery. Container Orchestration: Manage and scale containerized workloads using Kubernetes and Docker. Cloud Optimization: Monitor and optimize cloud resource usage for performance and cost efficiency. Site Reliability Engineering (SRE) Reliability Metrics: Define and maintain Service Level Objectives (SLOs) and Service Level Indicators (SLIs). Monitoring & Observability: Implement observability tools and dashboards (e.g., Prometheus, Datadog, Grafana) for real-time system monitoring. Incident Management: Lead incident response efforts, conduct root cause analysis, and implement actionable postmortem reviews. Infrastructure Management AWS Expertise: Architect and manage cloud-based systems to handle high-traffic, latency-sensitive applications. Disaster Recovery: Implement robust disaster recovery and business continuity strategies, including backups and multi-region failover. Security Practices: Collaborate with security teams to enforce best practices for IAM, encryption, and compliance. Collaboration & Leadership Cross-Team Collaboration: Partner with software engineers to design infrastructure solutions tailored to their application needs. Culture Building: Help shape the engineering culture, promoting a philosophy of security, velocity, and reliability. Mentorship: Mentor junior engineers and document best practices to drive knowledge sharing and operational excellence. Long-Term Tech Evolution Backend Transition: Contribute to evolving our backend microservices (currently NodeJS, with some Python and C#) towards Go and Rust. Third-Party Integration: Evaluate and integrate critical third-party software and infrastructure, such as payment gateways and mobility stacks. Your Impact: Simplify infrastructure concerns for product teams to accelerate builds, deployments, and scaling. Advocate for modern practices like Zero Trust Networking and continuously improve platform architecture. Balance the demands of product velocity with a well-managed, secure, and scalable platform. Required Skills & Experience: Technical Expertise Cloud Experience: 5-8+ years of hands-on experience with cloud platforms, particularly AWS, including services like EC2, RDS, S3, Lambda, and VPC. Containerization: Proficiency with Docker and Kubernetes (EKS) or ECS. Infrastructure as Code (IaC): Strong experience with Terraform, CloudFormation, or Pulumi. Programming Skills: Proficiency in at least one programming language (e.g., Python, Go, TypeScript/JavaScript, Ruby, Java). DevOps & SRE CI/CD Pipelines: Expertise in building and maintaining CI/CD workflows using tools like GitLab CI, Jenkins, or GitHub Actions. Monitoring Tools: Experience with observability platforms (e.g., Prometheus, Datadog, Grafana). Incident Management: Proven ability to handle incident response, root cause analysis, and postmortem reviews. Soft Skills Problem-Solving: Ability to research, design, and deliver solutions to complex infrastructure challenges. Collaboration: Experience working directly with product engineers to improve workflows incrementally. Leadership: Ownership mindset with the ability to mentor team members and advocate for best practices. Preferred Skills (Nice-to-Have): Familiarity with backend languages like Go or Rust. AWS certifications (e.g., Solutions Architect, DevOps Engineer). Experience with networking concepts (e.g., load balancers, DNS, VPNs) and traffic optimization. Knowledge of emerging CNCF technologies and CI/CD trends. What We Offer: Competitive salary with future equity options Opportunities to work with cutting-edge technologies and evolve our platform. Flexible working hours and a remote-friendly environment. Professional growth through certifications, conferences, and internal training. Collaborative culture focused on innovation and operational excellence.

Job Description Job Description Senior Software Engineer, Reliability Remote, US About Nametag Nametag is building the future of secure digital identity. Our mission is to make it easy for people and organizations to prove who they are online, safely and seamlessly. We're pioneering next-generation identity verification and account protection so that users can control their own identity, and companies can build trust without friction. By enabling trust at scale, we help enterprises reduce fraud, streamline onboarding, and deliver secure user experiences that customers love. The Role We're looking for a Senior Software Engineer to own infrastructure, reliability, and platform engineering at Nametag. You'll design and scale the systems that keep our identity verification platform fast, secure, and always available, and build the tooling that makes our engineering team more productive and autonomous. This is a hands-on, high-impact role. You'll work closely with engineering and product leadership to make critical decisions about how we build, deploy, and operate our systems, and then execute on them. If you've thrived in fast-moving environments and care deeply about uptime, correctness, and developer experience, we'd love to meet you. What You'll Do Infrastructure & Reliability Design, build, and maintain scalable, cost-effective cloud infrastructure across AWS and Fly.io. Own deployment strategy and service design across our monolith and microservices, including schema migrations and rollout safety. Manage infrastructure-as-code (CloudFormation, Terraform or equivalent) for reproducible, auditable infrastructure. Identify reliability risks, performance bottlenecks, and security gaps, and address them proactively. Observability & Incident Response Evolve our observability stack: logging, distributed tracing, metrics, and uptime monitoring. Evolve on-call practices and incident response processes that keep us ahead of customer-impacting issues. Champion a culture of reliability: postmortems, runbooks, and continuous improvement after incidents. Developer Enablement Manage and improve our CI/CD pipelines (GitHub Actions) and establish deployment best practices. Build internal platform tooling and abstractions that reduce toil and increase engineering velocity. Partner with product engineers to make infrastructure easy to use correctly and hard to use incorrectly. Data & ML Infrastructure Design and operate data pipelines that support our ML-powered verification systems. Evolve our MLOps infrastructure so models can be trained, evaluated, and deployed safely and repeatedly. Collaboration & Leadership Work closely with engineering and product leadership on technical roadmap decisions. Review code, mentor peers, and help raise the bar on security, reliability, and operational discipline. Communicate infrastructure tradeoffs clearly across technical and non-technical stakeholders. Ideal Qualifications Work Authorization (Required): Applicants must be legally authorized to work in the United States for any employer without current or future need for visa sponsorship. This is a firm requirement. The technical qualifications below are guidelines. We know that no candidate will perfectly match every requirement, and that's okay. If you're passionate about what we're building and have most of the skills below, we'd love to hear from you. Cloud & Infrastructure: Hands-on experience managing and securing cloud infrastructure. AWS required; Fly.io or similar a plus. Infrastructure-as-Code: Production experience with Terraform or equivalent tools. Databases: Deep experience with PostgreSQL, including schema design, migrations, and query performance tuning. CI/CD: Strong experience designing and managing pipelines, GitHub Actions preferred. Languages: Proficiency in modern, type-safe languages. Go strongly preferred. Observability: Experience building and operating logging, tracing, and metrics systems in production. MLOps & Data Pipelines: Prior experience shipping ML infrastructure into production, not just experimentation. Startup experience: You've worked at an early-stage company and know what it means to move fast without compromising the things that matter. Security: Security-minded by default. You design with the threat model in mind, not as an afterthought. What We Value Intellectual horsepower. Quickly grasping complex technical and business concepts. Kindness and integrity. Earning trust is central to how we build relationships with customers and colleagues. Bias for action. We move quickly to deliver impact and protect our customers against fast-moving threats. Ownership mindset. You care about uptime and stability the way a founder cares about the product. Compensation The base salary range for this full-time position is $120,000 to $190,000, plus equity and benefits. Nametag is a founding member of the Open Imperative, publicly committed to pay equity in the technology industry. We post positions with ranges to encourage people of different backgrounds and experiences to apply. Every offer is benchmarked against market data to ensure fairness and consistency. Final compensation is determined by role, level, and additional factors such as skills, experience, and education. Your recruiter or hiring manager can share more details during the hiring process. Culture & Perks At Nametag, we believe trust starts with how we treat each other. We're a remote-first team that values autonomy, inclusivity, and collaboration, with regular in-person time to stay connected and innovate together. Remote-first: Work from anywhere in the US. Our team spans Seattle, San Francisco, Ann Arbor, Denver, New York City, and beyond. Off-sites: We bring the team together once per quarter for in-person collaboration, often off-site in new places. Flexible schedules: Work in your own time zone; we align key meetings across a shared window. We Offer Competitive salary Meaningful equity ownership Comprehensive health benefits (medical, dental, vision) Flexible paid time off Quarterly team off-sites and travel support New computer hardware and equipment An inclusive environment where your voice has impact and your work drives change

Software Developer in Test (SDET) Automation & AI Frameworks Location: Foster City, CA (100% In-Person) Pay Rate: $65.21 / hour (Full-Time Contract) Schedule: Monday Friday, Day Shift (40 hours/week) Industry: Autonomous Mobility & Advanced Software Systems About the Opportunity Comrise is looking for a self driven, senior Software Developer in Test (SDET) to help build scalable automation frameworks from scratch and elevate testing infrastructure for mission critical web, cloud, backend, and mobile applications. If you are passionate about building robust regression suites, leveraging cutting-edge AI testing tools, and ensuring the absolute reliability of safety-critical technologies, this is your opportunity to drive end-to-end testing strategy in a high-impact environment. What You Will Do Framework Development: Design, build, and maintain scalable automation testing frameworks from the ground up for cloud, backend, and mobile applications. End-to-End Automation: Create automated tests covering APIs, integration, subsystem, and edge-case scenarios to minimize repetitive manual testing. AI-Driven Testing: Implement AI-powered tools and workflows to accelerate test execution, boost coverage, and optimize engineering pr ductivity. Cross-Team Collaboration: Partner with QA engineers and software development teams to refine validation workflows and drive the transition from manual strategy to robust automation. Quality & Performance: Develop regression suites, validate high-stress system scenarios, and enhance automated tooling usability for engineering teams. What We Are Looking For Experience: 5+ years of hands on experience as an SDET with a proven track record of architecting cloud and backend automation frameworks from scratch. Education: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related technical field. Technical Stack: Strong proficiency in Python, Kotlin, and modern CI/CD & version control tools like Git and Buildkite. Cloud & API Testing: Hands on experience building functional and performance automation for backend cloud environments and mobile apps. Bonus Skills: Hands-on experience with Playwright automation and implementing AI tools within the testing domain. Position Details & Work Environment Work Setting: 100% On-site in Foster City, CA (5 days/week in office). Facility Requirements: Ability to complete background checks and facility compliance requirements. Interview Process: 30-minute Manager Zoom $ightarrow$ 1.5-hour Panel Interview (includes an on-site portion). Ready to Apply? If you are ready to apply your automation expertise to complex, next-generation software platforms, click Apply Now to submit your resume for immediate review!

Job Title: Lead Network Support Engineer Overview / Summary HTC Global Services is seeking an experienced Lead Network Support Engineer (L3) to provide advanced technical leadership and serve as the final escalation point for complex network issues. This role includes network assessments, architecture support, firewall management, performance optimization, automation, and mentoring junior engineers. The engineer will be a core member of the assessment delivery team and transition into a lead technical role supporting the client's transformation from an SOP-based operating model to a self-healing infrastructure model. Work Location: Based out of the HTC Troy office. Must be available to travel to the client location in Buffalo, New York, on short notice as required. Key Responsibilities Assess FortiGate deployments, including FortiOS version currency, FortiManager/FortiAnalyzer integration, HA cluster configuration, SD-WAN posture, security fabric maturity, VPNs, and threat prevention profile alignment. Assess Palo Alto Networks deployments, including PAN-OS version currency, Panorama management, HA configuration, GlobalProtect VPN posture, App-ID/User-ID/Content-ID adoption, WildFire integration, and security policy layering. Review firewall change control processes, rule review cadence, and rulebase governance. Lead data center switching assessments across Cisco Nexus and Arista environments, including spine-leaf, VPC, MLAG, EVPN-VXLAN, rack build standards, cabling, capacity analysis, out-of-band management, and software version currency. Lead reviews of perimeter and network security controls, including firewall rule analysis, policy hygiene, security profiles, and configuration standardization. Support risk register development and 30-60-90-day remediation roadmaps. Develop standardized configuration templates and practice standards for switches, firewalls, network additions, rack builds, and change activities. Contribute to hardware lifecycle, firmware/software currency, and end-of-life/end-of-support reviews. Configure and work with SolarWinds and other monitoring tools. Perform network discovery activities. Apply knowledge of data center design patterns, including spine-leaf topology, ECMP, jumbo frames, storage traffic isolation, and out-of-band management. Act as the final L3 escalation point for complex network issues involving QoS, OSPF, BGP, VLANs, STP, port channels, NAT, ACLs, and VPNs. Perform packet and traffic analysis using Wireshark, FortiAnalyzer, Syslog, and related tools. Lead P1/P2 incident bridge calls, perform root cause analysis, and drive issue resolution. Support network discovery and CMDB tooling, including Device42, Lansweeper, ServiceNow Discovery, SolarWinds, or comparable platforms. Operate within a ServiceNow ITSM environment, supporting incident, change, problem, and CMDB workflows. Contribute to and review high-level and low-level network designs for new sites, migrations, segmentation initiatives, and firewall architectures. Validate network designs for scalability, security, and adherence to enterprise standards. Recommend improvements across routing, switching, wireless, and security environments. Manage and optimize Fortinet FortiGate environments, including policies, NAT, UTM profiles, VPNs, routing, and HA. Audit firewall rules for least-privilege access and compliance. Support segmentation, hardening, and compliance initiatives. Perform capacity planning, traffic analysis, performance tuning, and proactive network health monitoring. Develop and maintain automation scripts using Python, Bash, and EEM. Automate configuration backups, compliance checks, and monitoring integrations. Lead network changes, upgrades, firewall migrations, and routing redesigns. Prepare RFCs, rollback plans, risk assessments, and post-change reports. Coordinate with application, infrastructure, security, and ISP teams. Work with ISPs and OEMs, including Cisco and Fortinet, on escalations, TAC cases, and hardware issues. Validate circuit performance and support last-mile troubleshooting. Maintain network diagrams, SOPs, configuration standards, and runbooks. Improve L1/L2 documentation and operational processes. Mentor L1/L2 engineers and contribute to training, standards, and continuous improvement initiatives. Required Qualifications 10-12 years of networking experience, including 3-4 years in an L3 or Architect-level role. Extensive hands-on experience with Cisco IOS/XE and NX-OS. Strong expertise in routing (OSPF, BGP) and switching (VLANs, STP, EtherChannel). Experience with Fortinet FortiGate (FortiOS) and Palo Alto Networks firewalls. Experience with HA cluster configuration. Experience with SD-WAN posture, security fabric maturity, VPNs, and threat prevention profile alignment. Senior-level experience with Cisco Nexus 9000/7000/5000 series, NX-OS upgrades, VPC, VXLAN/EVPN, FEX topologies, out-of-band management, and greenfield rack builds. Strong experience with Meraki wireless. Experience with Cisco DNaC and Cisco ISE. Solid understanding of network security, VPNs, QoS, and network segmentation. Experience with NMS/SNMP monitoring, Syslog, and packet capture tools. Working knowledge of automation and scripting using Python, Bash, and EEM. Experience configuring SolarWinds and other monitoring tools. Experience performing network discovery. CCNA or equivalent hands-on experience (required). CCNP Enterprise (strongly preferred). Fortinet NSE 4 or higher (preferred). ITIL v4 Foundation (optional). Strong analytical and structured troubleshooting approach. Excellent communication during high-severity incidents. Proactive, detail-oriented, automation-focused, and collaborative mindset. Ability to mentor junior engineers. Ability to perform occasional lifting of network equipment (up to 50 lbs), if required. What Makes HTC A Great Place To Build Your Future HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies. At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks. Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected. Rhode Island, Washington, Washington DC,Vermont, California, Colorado, Connecticut, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New York, New Jersey, Nevada, Ohio PAY TRANSPARENCY TAGLINE: For information on the compensation range and an overview of benefits offered by HTC Global Services, please email: . Salary, other compensation, and benefits information shared by HTC are accurate as of the date provided. The disclosed range may vary based on factors such as geographic location, education, relevant experience, certifications, skills, role fit, organizational needs & other factors as applicable. HTC Global Services reserves the right to modify ranges in accordance with governmental, state, and local requirements.

Job Title: Senior z/OS System Programmer Main location(s): Chandler, AZ Manager open to candidates in other locations: Plano, TX / Charlotte, NC / Pennington, NJ / Jersey City, NJ Duration: Contract - 11 months Pay Range: $70.23/hr (W2) Job ID: 407697 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking a z/OS Systems Engineer to join our team. The ideal candidate will have strong experience in z/OS platform engineering, JES2 administration, SMP/E maintenance, and z/OS UNIX System Services and a proven ability to design, automate, and operate mainframe infrastructure aligned with enterprise standards. Responsibilities: Design, engineer, and maintain z/OS platform tools and services in alignment with architecture, governance, and security policies. Provide subject-matter expertise in z/OS infrastructure and deliver technical consultation and best practices to application, infrastructure, and engineering teams. Translate business and operational requirements into z/OS technical designs, deployment blueprints, standards, and runbooks. Develop and enhance automation, scripts, and tooling to eliminate manual tasks and improve reliability and efficiency. Create reusable templates and playbooks for standardized builds, configuration, deployment, and operations. Evaluate and validate third-party mainframe software and tools for enterprise adoption and compliance. Identify opportunities to improve performance, resiliency, and operational processes through modernization. Contribute to product and solution evaluations by defining functional and non-functional technical requirements. Support risk management, change management, and problem resolution in a regulated, high-availability environment. Provide technical guidance, mentoring, and leadership to junior staff and promote a collaborative team culture. Required Skills & Qualifications: Strong experience configuring, maintaining, and supporting z/OS, including release installation, maintenance, and management of PTFs, APARs, and USERMODs with SMP/E. Proficiency in developing and maintaining system utilities, exits, and automation using REXX and BAL/Assembler. Administration of z/OS UNIX System Services, including file systems, permissions, scripting, and zFS configuration and support. Hands-on experience configuring and supporting JES2, including job classes, initiators, spool tuning, and workload controls. Strong working knowledge of TSO/ISPF for system programming and operational tasks. Experience managing LPARs and processor resources using the Hardware Management Console (HMC). Ability to diagnose and resolve system-level issues, including abends, dumps, hardware errors, and performance problems using IPCS, EREP, and RMF. Preferred Skills: Experience defining and maintaining complex server, storage, and network configurations using Hardware Configuration Definition (HCD). Familiarity with enterprise evaluation of mainframe products and solution fit-for-purpose assessments. Additional Information Candidates should include current location and intent on the resume. Indicate if 18 months tenure is not available. GLIDER ID verification is required. Supplier process requires resume and candidate name with JP ID sent to SR PC for approval before posting submission. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits. Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume.

About the Role & Team: Walt Disney Imagineering makes the impossible possible, by combining innovation and storytelling to bring Disney stories, characters, and worlds to life. Imagineering is the master planning, creative development, design, engineering, production, project management, and research and development arm of The Walt Disney Company. Its talented Imagineers are responsible for the creation - from concept initiation through installation - of all Disney Resorts, theme parks and attractions, real estate developments, regional entertainment venues, and new media projects. Disney Imagineers are uniquely talented individuals who bring together the best aspects of creativity, innovation, and passion. At Imagineering Research and Development, our mission is to use technology to build new experiences for our Guests and new tools for Imagineers and the Cast Members who power our parks. R&D is a team of engineers, designers, artists, and scientists who share a passion for solving hard problems and building ground-breaking experiences. As the Estimating and Scope Management Tech Lead, you are the senior individual contributor and technical anchor for these capabilities. You set the technical direction, drive execution alongside our partner teams, and elevate the engineers around you. You think in user problems first: the Imagineers using these tools are the people across the table, not tickets in a backlog. This role reports to the Manager, Software Development and partners closely with product managers, project managers, and business stakeholders. This role will report directly to the Sr. Manager of Software Development. This is a Full-Time role. What You Will Do • Own the technical direction - architecture, design choices, and integration strategy. • Lead delivery end-to-end - find the real problem underneath the stated one, prove feasibility fast, and ship what's worth shipping. Estimate, plan, design, implement, and close out software work for assigned scope, balancing evolving requirements against fixed budgets and schedules. • Build and maintain whole feature sets - from desktop and web applications through cloud-scale services and the data pipelines that connect them. • Partner across the Studio - translate product and business needs into technical requirements with product managers, project leads, and partner engineering teams; communicate trade-offs and risk early. • Set the engineering bar - lead code reviews, define and uphold standards and processes within the portfolio and contribute to studio-wide practice. • Build at the frontier - stay current on the tools changing how software gets made (AI-assisted development, modern data platforms, new frameworks), and bring what works back to the team. Required Qualifications & Skills • 8+ years of professional software development experience, with a demonstrated track record of leading technical work. • Strong proficiency in one or more modern languages (e.g., TypeScript, C#, Python, Java, JavaScript). • Working knowledge of CI/CD, infrastructure as code (e.g., Terraform), containerization (Docker), AWS, and observability tooling (e.g., Datadog, Splunk). • Experience designing and operating full-stack systems in the cloud, with sound instincts for security, performance, and reliability. • Fluency with modern engineering practice - version control, code review, automated testing, and workflow tooling (Git, GitLab, GitHub, JIRA, Jenkins). • Excellent written and verbal communication, including the ability to document decisions and explain technical trade-offs to non-engineering partners. • Willingness to travel occasionally on behalf of the company. Preferred Qualifications • Experience building software for estimating, project controls, or other business-critical domains. • Depth in data modeling, ETL/data pipelines, and warehouse technologies (e.g., Snowflake). • Familiarity with reactive front-end frameworks (Vue.js preferred) and full-stack TypeScript/Node.js. • Experience integrating or extending vendor SaaS platforms and managing technical aspects of vendor relationships. • Proficiency with AI-assisted development workflows and tooling (e.g., Copilot, Cursor, Claude Code). Education • Bachelor's degree in computer science, software engineering, or a related field Required. Additional Information: Disney offers a rewards package to help you live your best life. This includes health and savings benefits, educational opportunities, and special extras that only Disney can provide. Learn more about our benefits and perks at . The hiring range for this position in Orlando, FL is $148,300.00-$198,800.00 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

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

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

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

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

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

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