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The Kubernetes Service Engineer will design, deploy, and operate service mesh platforms like Istio and Linkerd to ensure secure and reliable service-to-service communication. They will also develop adoption patterns, implement zero-trust security policies, and optimize mesh performance across multi-cluster environments.
The Principal Software Engineer will design high-scale distributed systems and lead cross-team technical initiatives. They are responsible for shaping engineering culture and mentoring senior engineers while driving architectural decisions at an enterprise scale.
The Lead .NET Full Stack Engineer will design, build, and maintain enterprise-grade web applications and distributed systems using Microsoft technology stacks. The role encompasses the full engineering lifecycle, including architectural design, hands-on implementation, code reviews, and deployment.
The MuleSoft Integration Engineer will design, build, and operate enterprise integration solutions on the MuleSoft Anypoint Platform. They will own the full integration lifecycle, including API development, deployment, and ongoing optimization while collaborating with cross-functional teams.
Design and develop integrations between Coupa and various enterprise systems including ERP, finance, and HR platforms. Manage supplier onboarding, invoicing, and payment integrations while ensuring secure API performance and data synchronization.
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Design, develop, and maintain modular, composable Terraform code to codify infrastructure across cloud environments. Implement automation pipelines and enforce policy-as-code to ensure secure, compliant, and scalable infrastructure delivery.
Design, build, and integrate software systems for autonomous robots and robotic platforms. Collaborate with cross-functional teams to translate requirements into engineered solutions while mentoring junior engineers.
The Microservices Architect will lead the design and evolution of large-scale microservices ecosystems using cloud-native technologies and domain-driven design. They are responsible for defining architecture standards, modernizing legacy monoliths, and ensuring system resilience and scalability.
The ML Platform Engineer will design, build, and operate high-performance inference platforms for serving large machine learning models in production. Responsibilities include optimizing GPU utilization, implementing autoscaling, and ensuring end-to-end observability for diverse model workloads.
The engineer will design, build, and operate the platform layer for large-scale AI training and inference workloads. Responsibilities include managing GPU clusters, optimizing distributed training frameworks, and ensuring high reliability and efficiency of AI infrastructure.
The Lead Backend Developer will design, build, and operate foundational platforms and shared services to support high-throughput engineering needs. This role involves managing request routing, traffic management, caching layers, and durable event processing to ensure system scalability and reliability.
The PLM Engineer will own the technical operation of the PLM platform, including installation, configuration, performance tuning, and upgrades. They will also partner with functional, engineering, and manufacturing teams to ensure a reliable, performant, and secure PLM ecosystem.
Design and implement reinforcement learning solutions for sequential decision-making problems in real and simulated environments. Develop scalable training infrastructure and monitor deployed models for performance, drift, and safety.
The Quantitative Developer will build low-latency, high-reliability trading, risk, and analytics systems for fintech applications. They will partner with quants and traders to translate mathematical models into production-quality software.
The developer will perform deep, low-level Windchill customizations using Java and PTC APIs while maintaining an upgrade-friendly architecture. They will collaborate with cross-functional teams to translate requirements into engineered solutions and provide mentorship to junior engineers.
The ML Security Engineer will lead the design and implementation of security controls, threat models, and incident response capabilities for AI and machine learning systems. They will also secure training pipelines, perform red-team exercises, and ensure compliance with regulatory obligations.
The Platform Reliability Engineer will ensure the availability, performance, and operational excellence of large-scale distributed systems. They will apply software engineering principles to infrastructure and operations to push the platform toward higher reliability and lower operational toil.
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The Lead Backend Engineer will design, build, and operate large-scale, high-throughput backend services for mission-critical workloads. They will architect core platforms while focusing on scalability, reliability, performance, and clean engineering practices.
The Enterprise Data Architect will define and lead the architecture of the enterprise data platform, covering ingestion, storage, processing, and consumption. They will establish data modeling standards and partner with cross-functional teams to deliver a scalable, secure, and coherent data foundation.
The ServiceNow Developer will build and maintain solutions across ITSM, ITOM, HRSD, CSM, and custom scoped applications. This role involves hands-on configuration, scripting, and integration work while ensuring the platform remains upgrade-safe and performant.
The Site Observability Engineer will design and operate enterprise-grade observability platforms, including metrics, logging, tracing, and alerting systems. They will also define SLOs and SLIs while building self-service tooling to help engineering teams maintain system reliability.
The developer will build and maintain solutions across various ServiceNow modules including ITSM, ITOM, HRSD, and CSM. They are responsible for hands-on configuration, scripting, and platform integrations while ensuring the system remains performant and upgrade-safe.
Design and build production-grade Salesforce solutions using Apex, Lightning Web Components, and Flow. Manage custom business logic, integrations, and automation while ensuring platform maintainability.
The developer will design, build, and operate integrations connecting PTC Windchill with ERP, MES, CAD, and other enterprise systems. They will own the technical integration layer and collaborate with cross-functional teams to translate requirements into engineered solutions.
The Streaming Data Engineer will architect, deploy, and operate large-scale Apache Kafka and Confluent platform environments for mission-critical workloads. They will own the platform end-to-end, including cluster configuration, security, automation, and developer enablement.
Design, develop, and maintain complex Workday integrations using EIB, Studio, and various APIs to connect enterprise systems. Collaborate with cross-functional stakeholders to translate business requirements into reliable, secure, and well-documented integration solutions.
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Design, develop, and support customizations, integrations, and enhancements on the Windchill PLM platform. Collaborate with cross-functional partners to translate manufacturing and product-lifecycle requirements into well-engineered solutions.
The Staff Software Engineer will lead complex, cross-team engineering initiatives and drive platform modernization efforts. They are responsible for providing technical leadership, mentoring senior engineers, and ensuring operational excellence across large-scale systems.
The Secure AI Systems Engineer will lead the design and implementation of security controls and threat models for AI and machine learning systems. This role focuses on mitigating risks such as prompt injection, model abuse, and data exfiltration within LLMs and AI infrastructure.
The Secure Software Engineer will embed security throughout the software development lifecycle by partnering with engineering teams to design secure systems. They are responsible for identifying vulnerabilities and reducing risk across the company's application portfolio.
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