Lead Engineer 2c Process Development Core Engineering Module Jobs

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. You will work remotely from Germany and will be reporting to Sr. Director, Engineering You Will: Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer's workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn't done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to so

What you’ll do Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability. Own core runtime foundations: distributed control, state management, fault handling, and reliability. Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes. Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints). Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes. Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress. What we’re looking for Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products. Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering). Track record of shipping systems that are observable, debuggable, and resilient. Strong technical leadership: clarity, pragmatic trade-offs, and mentoring. Useful experience Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling. High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review. Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior. Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI. Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a Rack Power Engineer with deep expertise in high-power conversion and distribution to design, qualify, and support power systems for AI supercomputers. You will own rack power solutions—including power shelves, AC/DC rectifiers, power supply units (PSUs), power management controllers (PMCs), and high-current distribution—from requirements and supplier development through deployment. You will also monitor fleet rack power health, lead debugging and root-cause investigations, and drive improvements into hardware, firmware, and qualification coverage. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own rack power architecture and requirements for high-power AI supercomputing systems, including power budgets, AC input interfaces, DC distribution, redundancy, efficiency, serviceability, and integration with data center infrastructure. Drive the design and supplier development of power shelves, rectifiers, PSUs, PMCs, busbars, connectors, and protection circuits. Review electrical designs and control behavior, and evaluate performance, cost, reliability, and availability trade-offs. Define and execute component, shelf, and rack qualification plans covering load transients, current sharing, hot-swap, startup and shutdown, redundancy failover, fault protection and recovery, thermal limits, and AC disturbances and ride-through

Leidos is seeking a Test and Integration Engineer to lead cutting-edge testing and validation efforts within the Undersea Systems Division (USD) . This role is a unique opportunity to drive innovation in testing underwater vehicle systems, maritime sensors, subsea telemetry, and ISR solutions that support critical defense and national security missions. You'll contribute to a multidisciplinary team focused on testing, integrating, and validating advanced maritime technologies, ensuring system reliability and performance from prototype design to full-scale system deployment for ongoing Navy missions. Leidos’ Undersea Systems Division is a recognized leader in C4ISR technologies, delivering innovative, mission-critical solutions across sensor networks, unmanned systems, and tactical platforms . We’re known for achieving “industry firsts” in the most challenging maritime domains. Join us and be part of a world-class team delivering unmatched solutions for today's most pressing maritime missions. Why Join Us? Make an Impact : Your work will directly support U.S. maritime dominance and national security. Lead Innovation : Be at the forefront of applying innovative technology and autonomy to real-world maritime systems. Work with Experts : Collaborate with a top-tier team of engineers, scientists, and technicians located across the U.S. Shape the Future : Influence both the strategic and tactical direction of next-generation subsea technologies. What You’ll Do Test and Validate: Write, develop and execute comprehensive test plans, procedures, and protocols to ensure system functionality, reliability, and compliance with requirements. Integrate systems and conduct hands-on testing: Write, develop, and execute integration plans to bring complex systems together. Perform field</b

AI Engineer - Enterprise Search Overview We are looking for an experienced Enterprise Search Lead to build and optimize our multi-tenant enterprise search solution. This role focuses on creating scalable systems that integrate seamlessly with customer environments, leveraging cutting-edge AI and ML technologies. You will design and manage the enterprise knowledge graph, implement personalized search experiences, and drive AI- powered innovations to enhance search relevance and ITSM workflows. What You Will Do: Build and structure our enterprise knowledge graph to organize content, people, and activity into meaningful relationships for better search relevance. Develop and refine personalized ranking models that adapt to user behavior and improve search results over time. Design ways to adapt AI language models to each customerʼs data for enhanced accuracy and context. Explore innovative methods to combine LLMs with search engines for answering complex queries Write clean, robust, and maintainable code that integrates smoothly with multi-tenant systems. Collaborate with cross-functional teams to align search capabilities with ITSM workflows. Mentor junior engineers or learn from experienced ones to grow as a technical leader. What You Should Have 3-5 years of experience working on enterprise search products with AI/ML integration. Expertise in multi-tenant systems and securely integrating with external customer systems. Hands-on experience with tools like Elasticsearch, Solr, or similar search platforms. Strong coding skills in Python, Java, or equivalent languages. A passion for solving complex problems with AI and delivering intuitive user experiences. Important notice for candidates: Job scams are on the rise. Please keep these guidelines in mind when applying for any open roles at Atomicwork. Only apply through official Atomicwork channels. We do not use third-party agencies or individuals who ask for payments in exchange for interviews or offer letter

Staff Engineer - Enterprise Search Overview We are looking for an experienced Enterprise Search Lead to build and optimize our multi-tenant enterprise search solution. This role focuses on creating scalable systems that integrate seamlessly with customer environments, leveraging cutting-edge AI and ML technologies. You will design and manage the enterprise knowledge graph, implement personalized search experiences, and drive AI-powered innovations to enhance search relevance and ITSM workflows. What You Will Do Build and structure our enterprise knowledge graph to organize content, people, and activity into meaningful relationships for better search relevance. Develop and refine personalized ranking models that adapt to user behavior and improve search results over time. Design ways to adapt AI language models to each customer’s data for enhanced accuracy and context. Explore innovative methods to combine LLMs with search engines for answering complex queries. Write clean, robust, and maintainable code that integrates smoothly with multi-tenant systems. Collaborate with cross-functional teams to align search capabilities with ITSM workflows. Mentor junior engineers or learn from experienced ones to grow as a technical leader. What You Should Have 5+ years of experience working on enterprise search products with AI/ML integration. Expertise in multi-tenant systems and securely integrating with external customer systems. Hands-on experience with tools like Elasticsearch, Solr, or similar search platforms. Strong coding skills in Python, Java, or equivalent languages. A passion for solving complex problems with AI and delivering intuitive user experiences. Important notice for candidates: Job scams are on the rise. Please keep these guidelines in mind when applying for any open roles at Atomicwork. Only apply through official Atomicwork channels. We do not use third-party agencies or individuals wh

You’ll shape the future of a business‑critical platform as the technical lead across both product engineering and cloud infrastructure. You’ll modernize a mature .NET application running on AWS today, while steering its evolution toward a cloud‑native, React/Node.js, AI‑enabled architecture. If you enjoy owning architecture end‑to‑end, from backend and frontend through CI/CD, DevOps, and AWS infrastructure, this role gives you real influence at Staff Engineer level and the opportunity to set engineering standards that others follow. You’ll spend your time leading complex .NET and React features, designing scalable AWS infrastructure with Infrastructure as Code, and building automation that makes releases fast, safe, and repeatable. You’ll work on performance, reliability, and modernization in equal measure—fixing what’s slowing the platform down today and designing what it will look like in the next generation. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture and development of enterprise .NET services and APIs that power a business‑critical platform. Design and operate AWS infrastructure (using AWS CDK in TypeScript) to support secure, scalable, multi‑environment deployments. Build and optimize CI/CD pipelines (AWS CodePipeline, CodeBuild, Windows build agents) to make shipping .NET and React changes fast and reliable. Drive modernization initiatives across the stack, including clean architecture, refactoring legacy components, and reducing technical debt. Design and tune PostgreSQL and MSSQL database solutions for performance, scalability, and reliability. Mentor engineers and influence engineering practices across teams, raising the bar on cloud, DevOps, and software design. These are the essentials you’ll need to get an interview Significant experience (typically 8+ years) delivering and operating scalable enterprise software, owning both application code and cloud infrastructure. Deep hands‑on expertise with C

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, AI INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, AI INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re hiring a Staff Machine Learning Engineer to help drive the future of merchant presence and shopping experiences on Pinterest. This role sits on the Merchant team and focuses on building AI/ML systems (including LLMs) that identify, understand, and surface relevant, high-quality merchants across segments—so Pinners can discover new brands with greater confidence and consideration, and merchants can reach new, diverse audiences. In this role, you’ll lead LLM-first, evaluation-driven initiatives—near-term focused on agentic workflows, measurement, and operational rigor that strengthen Merchant Integrity and Business Integrity. Longer term, you’ll help advance core relevance capabilities such as merchant/brand affinity modeling and related signals that improve shopping discovery across Pinterest. You’ll partner closely with Product Managers, E