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  <jobs>
    <job>
      <externalid>de168cba-02c</externalid>
      <Title>Principal Software Engineer, Platform Security</Title>
      <Description><![CDATA[<p>We&#39;re looking for a principal-level engineer to serve as a technical leader for platform security across Anduril. This role combines deep expertise in cryptography, systems security, and secure architecture with the ability to drive security strategy across business lines and the platform.</p>
<p>As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.</p>
<p>Key Responsibilities:</p>
<ul>
<li>Own the technical vision and architecture for platform security across Anduril&#39;s product ecosystem</li>
<li>Design cryptographic systems, protocols, and key management architectures for autonomous and robotic platforms operating in contested and disconnected environments</li>
<li>Lead the design of hardware root-of-trust architectures integrating TPMs, TEEs, HSMs, and secure boot across diverse embedded platforms</li>
<li>Drive the strategy for promoting business-line security implementations into shared, composable platform services</li>
<li>Serve as the senior technical authority for security architecture reviews across the organization, providing definitive guidance on cryptographic design, protocol security, and system hardening</li>
<li>Define security patterns, reference architectures, and engineering standards that enable teams across Anduril to build securely and independently</li>
<li>Mentor and develop senior engineers on the team, raising the bar for security engineering across the organization</li>
<li>Represent Anduril&#39;s security engineering capabilities to customers, partners, and auditors when deep technical credibility is required</li>
<li>Evaluate emerging threats, cryptographic standards, and security technologies, driving adoption where they strengthen the platform</li>
</ul>
<p>Required Qualifications:</p>
<ul>
<li>12+ years of experience in software engineering, with significant depth in systems security and cryptography</li>
<li>Expert-level knowledge of cryptographic protocol design, including key management architectures, certificate systems, and cryptographic agility</li>
<li>Deep experience with hardware security: TPM, TEE, HSM, secure boot, and hardware root-of-trust design across multiple platform types</li>
<li>Proficient in two or more of: C++, Rust, Go</li>
<li>Experience designing security architectures for embedded, real-time, or robotic systems with constrained environments</li>
<li>Track record of leading cross-organizational technical initiatives and driving architectural decisions that span multiple teams</li>
<li>Strong ability to communicate complex security concepts to engineering leadership, product teams, and external stakeholders</li>
<li>Experience performing and leading threat modeling, security architecture reviews, and cryptographic design reviews</li>
<li>Eligible to obtain and maintain active U.S. Secret security clearance</li>
</ul>
<p>Preferred Qualifications:</p>
<ul>
<li>Experience with post-quantum cryptography, distributed key generation (DKG), or threshold cryptographic schemes</li>
<li>Background in defense, aerospace, or autonomous systems with exposure to FIPS 140, Common Criteria, or NSA CSfC requirements</li>
<li>Experience designing secure communication protocols for autonomous platforms or mesh networks</li>
<li>Deep knowledge of Linux kernel security, mandatory access controls (SELinux/AppArmor), and OS hardening at scale</li>
<li>Experience building and evolving platform security services consumed by dozens of teams</li>
<li>Familiarity with compliance frameworks (STIGs, NIST 800-53, CMMC) and translating them into engineering controls that don&#39;t compromise developer velocity</li>
<li>Publications, patents, or recognized contributions in cryptography or systems security</li>
<li>Experience with Nix build systems and reproducible build pipelines for security-critical software</li>
</ul>
<p>US Salary Range: $254,000-$336,000 USD</p>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>senior</Experiencelevel>
      <Workarrangement>onsite</Workarrangement>
      <Salaryrange>$254,000-$336,000 USD</Salaryrange>
      <Skills>cryptography, systems security, secure architecture, cryptographic protocol design, key management architectures, certificate systems, cryptographic agility, hardware security, TPM, TEE, HSM, secure boot, hardware root-of-trust design, embedded systems, real-time systems, robotic systems, constrained environments, cross-organizational technical initiatives, architectural decisions, complex security concepts, threat modeling, security architecture reviews, cryptographic design reviews, U.S. Secret security clearance, post-quantum cryptography, distributed key generation, threshold cryptographic schemes, defense, aerospace, autonomous systems, FIPS 140, Common Criteria, NSA CSfC requirements, secure communication protocols, mesh networks, Linux kernel security, mandatory access controls, OS hardening, compliance frameworks, STIGs, NIST 800-53, CMMC, publications, patents, recognized contributions, Nix build systems, reproducible build pipelines</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Anduril Industries</Employername>
      <Employerlogo>https://logos.yubhub.co/andurilindustries.com.png</Employerlogo>
      <Employerdescription>Anduril Industries is a defense technology company that transforms U.S. and allied military capabilities with advanced technology.</Employerdescription>
      <Employerwebsite>https://www.andurilindustries.com/</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://job-boards.greenhouse.io/andurilindustries/jobs/5087992007</Applyto>
      <Location>Boston, Massachusetts, United States; Costa Mesa, California, United States; Seattle, Washington, United States; Washington, District of Columbia, United States</Location>
      <Country></Country>
      <Postedate>2026-04-18</Postedate>
    </job>
    <job>
      <externalid>a51375e8-30e</externalid>
      <Title>Member of Technical Staff, Software Co-Design AI HPC Systems</Title>
      <Description><![CDATA[<p>Our team&#39;s mission is to architect, co-design, and productionize next-generation AI systems at datacenter scale. We operate at the intersection of models, systems software, networking, storage, and AI hardware, optimizing end-to-end performance, efficiency, reliability, and cost. Our work spans today&#39;s frontier AI workloads and directly shapes the next generation of accelerators, system architectures, and large-scale AI platforms. We pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures. This role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale. In addition to delivering real-world impact on large-scale AI platforms, the team actively contributes to the broader research and engineering community. Our work aligns closely with leading communities in ML systems, distributed systems, computer architecture, and high-performance computing, and we regularly publish, prototype, and open-source impactful technologies where appropriate.</p>
<p>About the Team</p>
<p>We build foundational AI infrastructure that enables large-scale training and inference across diverse workloads and rapidly evolving hardware generations. Our work directly shapes how AI systems are designed, deployed, and scaled today and into the future. Engineers on this team operate with end-to-end ownership, deep technical rigor, and a strong bias toward real-world impact.</p>
<p>Microsoft Superintelligence Team</p>
<p>Microsoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>
<p>This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!</p>
<p>Responsibilities</p>
<p>Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks. Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements. Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems. Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps. Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations. Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs. Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams. Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.</p>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>staff</Experiencelevel>
      <Workarrangement>hybrid</Workarrangement>
      <Salaryrange></Salaryrange>
      <Skills>AI accelerator or GPU architectures, Distributed systems and large-scale AI training/inference, High-performance computing (HPC) and collective communications, ML systems, runtimes, or compilers, Performance modeling, benchmarking, and systems analysis, Hardware–software co-design for AI workloads, Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development, Experience designing or operating large-scale AI clusters for training or inference, Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications, Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand), Background in performance modeling and capacity planning for future hardware generations, Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews, Publications, patents, or open-source contributions in systems, architecture, or ML systems</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Microsoft AI</Employername>
      <Employerlogo>https://logos.yubhub.co/microsoft.ai.png</Employerlogo>
      <Employerdescription>Microsoft AI is a technology company that develops and markets software products and services. It is one of the largest and most successful technology companies in the world.</Employerdescription>
      <Employerwebsite>https://microsoft.ai</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://microsoft.ai/job/member-of-technical-staff-software-co-design-ai-hpc-systems-mai-superintelligence-team-3/</Applyto>
      <Location>London</Location>
      <Country></Country>
      <Postedate>2026-03-08</Postedate>
    </job>
    <job>
      <externalid>cd1a0d16-311</externalid>
      <Title>Member of Technical Staff, Software Co-Design AI HPC Systems</Title>
      <Description><![CDATA[<p>Our team&#39;s mission is to architect, co-design, and productionize next-generation AI systems at datacenter scale. We operate at the intersection of models, systems software, networking, storage, and AI hardware, optimizing end-to-end performance, efficiency, reliability, and cost.</p>
<p>We pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures.</p>
<p>This role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale.</p>
<p>In addition to delivering real-world impact on large-scale AI platforms, the team actively contributes to the broader research and engineering community. Our work aligns closely with leading communities in ML systems, distributed systems, computer architecture, and high-performance computing, and we regularly publish, prototype, and open-source impactful technologies where appropriate.</p>
<p>Microsoft Superintelligence Team
Microsoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>
<p>This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact.</p>
<p>Responsibilities
Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks.</p>
<p>Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements.</p>
<p>Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems.</p>
<p>Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps.</p>
<p>Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations.</p>
<p>Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs.</p>
<p>Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams.</p>
<p>Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.</p>
<p>Qualifications
Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.</p>
<p>Additional or Preferred Qualifications
Master’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.</p>
<p>Strong background in one or more of the following areas: AI accelerator or GPU architectures Distributed systems and large-scale AI training/inference High-performance computing (HPC) and collective communications ML systems, runtimes, or compilers Performance modeling, benchmarking, and systems analysis Hardware–software co-design for AI workloads Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development.</p>
<p>Proven ability to work across organizational boundaries and influence technical decisions involving multiple stakeholders. Experience designing or operating large-scale AI clusters for training or inference. Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications. Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand). Background in performance modeling and capacity planning for future hardware generations. Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews. Publications, patents, or open-source contributions in systems, architecture, or ML systems are a plus.</p>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>staff</Experiencelevel>
      <Workarrangement>hybrid</Workarrangement>
      <Salaryrange>$139,900 – $274,800 per year</Salaryrange>
      <Skills>C, C++, C#, Java, JavaScript, Python, AI accelerator or GPU architectures, Distributed systems and large-scale AI training/inference, High-performance computing (HPC) and collective communications, ML systems, runtimes, or compilers, Performance modeling, benchmarking, and systems analysis, Hardware–software co-design for AI workloads, Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development, LLMs, multimodal models, or recommendation systems, and their systems-level implications, Accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand), Performance modeling and capacity planning for future hardware generations, Contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews, Publications, patents, or open-source contributions in systems, architecture, or ML systems</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Microsoft AI</Employername>
      <Employerlogo>https://logos.yubhub.co/microsoft.ai.png</Employerlogo>
      <Employerdescription>Microsoft AI is a technology company that develops and markets software products and services. It is one of the largest and most successful technology companies in the world.</Employerdescription>
      <Employerwebsite>https://microsoft.ai</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://microsoft.ai/job/member-of-technical-staff-software-co-design-ai-hpc-systems-mai-superintelligence-team-2/</Applyto>
      <Location>Redmond</Location>
      <Country></Country>
      <Postedate>2026-03-08</Postedate>
    </job>
    <job>
      <externalid>4b5aec44-56d</externalid>
      <Title>Applied AI Engineer (Startups)</Title>
      <Description><![CDATA[<p>As an Applied AI Engineer on the Startups team at Anthropic, you will be a trusted technical advisor helping the top AI-native startups build on the Claude Developer Platform as they grow from early product to scale. You&#39;ll lead deep technical engagements, partnering directly with startup engineering teams to help them develop their products on top of Claude—advising on implementation, agent design, and working alongside them to build at the frontier of AI.</p>
<p>Working closely with Applied AI Architects, Account Executives, and Anthropic&#39;s Product and Engineering teams, you&#39;ll guide startups through deep technical engagements. You&#39;ll leverage your AI engineering expertise to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable startups to succeed with Claude.</p>
<p>You will serve as a deep technical advisor to high-potential startups, working alongside them to build innovative use cases that push the boundaries of AI. You will work hands-on with startup engineering teams: pair programming, architecture reviews, and code contributions that accelerate their development.</p>
<p>You will develop prototypes and technical documentation—including evaluation suites, AI engineering techniques, and architecture diagrams—that enable startups to build and scale with Claude. You will collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements.</p>
<p>You will identify patterns across engagements and contribute insights back to Product, Engineering, and the broader Applied AI team. You will create technical content for startup audiences including documentation, tutorials, and sample code. You will foster community engagement through hackathons, webinars, technical office hours, and startup-focused events.</p>
<p>You will travel to customer sites for workshops, implementation support, and relationship building. You will be a builder credibility that earns trust with technical founders and engineering teams—you&#39;ve shipped products and can speak from experience.</p>
<p>You will have strong technical communication skills with the ability to translate complex AI concepts into architectural decisions and actionable implementation plans. You will have experience facilitating technical workshops, hackathons, or developer-focused events. You will have passion for making powerful technology safe and beneficial.</p>
<p>The annual compensation range for this role is £225,000 - £240,000GBP.</p>
<p style="margin-top:24px;font-size:13px;color:#666;">XML job scraping automation by <a href="https://yubhub.co">YubHub</a></p>]]></Description>
      <Jobtype>full-time</Jobtype>
      <Experiencelevel>senior</Experiencelevel>
      <Workarrangement>hybrid</Workarrangement>
      <Salaryrange>£225,000 - £240,000GBP</Salaryrange>
      <Skills>AI engineering, Python, LLM-powered applications, agent architectures, evaluation frameworks, deployment at scale, pair programming, architecture reviews, code contributions, custom evaluation frameworks, scalable architectures, technical documentation, evaluation suites, AI engineering techniques, architecture diagrams</Skills>
      <Category>Engineering</Category>
      <Industry>Technology</Industry>
      <Employername>Anthropic</Employername>
      <Employerlogo>https://logos.yubhub.co/anthropic.com.png</Employerlogo>
      <Employerdescription>Anthropic&apos;s mission is to create reliable, interpretable, and steerable AI systems. The company is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</Employerdescription>
      <Employerwebsite>https://job-boards.greenhouse.io</Employerwebsite>
      <Compensationcurrency></Compensationcurrency>
      <Compensationmin></Compensationmin>
      <Compensationmax></Compensationmax>
      <Applyto>https://job-boards.greenhouse.io/anthropic/jobs/5116274008</Applyto>
      <Location>London, UK</Location>
      <Country></Country>
      <Postedate>2026-03-08</Postedate>
    </job>
  </jobs>
</source>