DDN

Design and debug LustreFS features, investigate cross-layer customer and scale issues, and improve storage performance, reliability, and observability. | Requires 10+ years in systems, storage, distributed systems, kernel, or filesystem engineering, with strong LustreFS, C, Linux debugging, and kernel expertise. | We are seeking a Staff Engineer with 10+ years of experience in distributed storage and Linux-based systems engineering. This is a hands-on senior technical role focused on design, debugging, performance, and operational excellence across LustreFS and adjacent stack components. The ideal candidate brings strong expertise in one or more Lustre subsystems, can independently drive complex investigations, and collaborates effectively across engineering, QE, support and release teams. Engineers who are comfortable using AI to accelerate triage, debugging, code comprehension and new feature design will be especially valuable. Key Responsibilities Design, develop and debug LustreFS features, fixes and enhancements across relevant subsystems such as llite, MDS/MDT, OSS/OST, LDLM and LNet. Investigate customer and scale-related defects, drive root-cause analysis and implement high-quality fixes with strong attention to correctness and maintainability. Contribute to performance tuning, failure analysis and reliability improvements for large-scale Lustre deployments. Participate actively in code reviews, design reviews and subsystem discussions, bringing rigor to testing and operational readiness. Work closely with QE and support to reproduce issues, improve diagnostic data quality and increase coverage for high-risk failure scenarios. Help document subsystem behavior, debugging approaches, known failure patterns and operational best practices. Use AI-assisted tools where appropriate to speed up issue triage, summarize logs, improve code understanding and capture reusable lessons learned. Required Qualifications 10+ years of experience in systems software, distributed systems, storage, Linux kernel or filesystem engineering. Strong experience in LustreFS development, support or performance engineering with depth in at least one major subsystem. Strong C programming and Linux systems debugging skills. Working knowledge of Linux kernel internals, filesystem semantics, networking and performance analysis. Experience with LNet and/or high-performance transports such as RDMA, InfiniBand, RoCE or TCP-based storage networking. Ability to debug and resolve issues spanning multiple layers including client, server, network and backend storage. Strong collaboration skills and the ability to work across functions in a fast-moving engineering environment. Preferred Skills Experience in HPC, AI infrastructure or large-scale parallel storage environments. Exposure to metadata-heavy and throughput-heavy workload characterization and tuning. Familiarity with ZFS, ldiskfs, NVMe-backed storage and related observability / performance tooling. Experience creating test plans, reproducer frameworks, runbooks or diagnostic automation. Comfort using AI tools to accelerate debugging, code reviews, triage, documentation and early-stage design ideation. Experience mentoring junior engineers or leading focused technical efforts within a subsystem. What You Will Work On Hands-on development and debugging of LustreFS defects, performance issues and subsystem enhancements. Customer-facing and scale-related issue investigation across llite, metadata, object storage, LNet and transport layers. Collaborative design and implementation of reliability, observability and serviceability improvements. Reviewing and validating fixes through targeted tests, failure injection, log analysis and performance characterization. Using AI-assisted workflows to accelerate triage, debug loops, code understanding and documentation quality. Contributing to team redundancy by strengthening documentation, code review quality and subsystem knowledge sharing. Why This Role Matters This role is central to building durable engineering redundancy in LustreFS: expanding deep subsystem ownership, reducing concentration risk, and accelerating next-generation delivery through strong engineering fundamentals and AI-enabled execution.

Lead design, development, and support of integrations and AI-enabled workflows across Order-to-Cash systems. | 5+ years integration development with Salesforce and Workato expertise and technical leadership. | Role summary The Staff Integrations and AI Engineer (Order-to-Cash) will be the technical lead for integrations across DDN’s Order to Cash ecosystem. This hands-on role will partner closely with Deal Desk, Order Management, Fulfillment, Billing, and Revenue stakeholders while serving as a primary technical lead in support of our GTM Business Systems team to design, build, support, and evolve secure, scalable integrations and automations in Order-to-Cash You will balance proven integration patterns with modern API-driven automation, including AI-enabled workflows, in a fast-paced and evolving environment. What you’ll do Lead the end-to-end design, development, testing, deployment, and support of integrations between SFDC and downstream finance and fulfillment systems, vendors, and enterprise platforms Partner directly with Deal Desk, Order Management, Fulfillment, Billing, Revenue, and GTM Business Systems stakeholders to translate business needs into clear, supportable technical designs and data flows Build and enhance integrations using SFDC tools like Platform Events, Change Data Capture, SOQL, and Bulk API Develop integrations and automations using REST and SOAP APIs, JSON, XML, and GraphQL where appropriate Use integration-platform-as-a-service technologies, including Workato, to orchestrate workflows across SFDC and adjacent systems such as Oracle EBS and Workday Financials Provide technical leadership and pragmatic guidance on best choice integration ( iPaaS, Google Cloud Functions, Flows, etc…) tool for Order data movement depending on the use case Design innovative, API-based automations that responsibly incorporate AI capabilities while maintaining strong security, reliability, and operational controls Own integration troubleshooting, monitoring, root-cause analysis, and production support; improve resiliency, observability, and documentation over time Establish and maintain technical specifications, field mappings, test plans, deployment runbooks, and integration documentation Participate in Workato release-impact analysis and testing, identifying enhancements and risks across the integration landscape What we’re looking for 5+ years of hands-on integration development experience, with a strong focus on SFDC, Workato (Preferred), and Order-to-Cash Demonstrated experience leading integration work from requirements through design, development, testing, deployment, and post-production support Practical expertise with Workato, SOQL, Bulk API, Platform Events and Change Data Capture, and SFDC security Natural curiosity and desire to learn, grow, and share. Strong experience with XML, JSON, REST APIs, SOAP APIs, and API-based system integration patterns Experience with iPaaS technologies, preferably Workato or a comparable platform. Solid understanding of Order-to-Cash business processes and data domains, such as Opportunity Management, Quoting, Order Management, Fulfillment, and Billing Strong customer service and ability to communicate technical concepts, data tradeoffs, and delivery risks clearly to both business and technical partners. Strong analytical and problem-solving skills, with a high level of ownership and attention to data quality, security, and reliability Comfortable operating in a global and fast-paced environment, prioritizing across concurrent initiatives, and moving between standard connector implementations and novel automation challenges Nice to have Experience building AI-enabled workflows through APIs, including safe and scalable integration of AI services into business processes Experience with Claude Code, command-line tooling, or developer productivity automation Experience supporting global or multi-country finance and sales environments Current or prior Workato Certification