Datadog's Software Engineers with Systems depth leverage their experience with systems and tooling to build software that ensures Datadog remains reliable, performant, and secure. For this track, their Software Engineering experience may resemble the Distributed Systems track, but is typically applied in combination with their systems experience to build and run internal platforms and tools that our products are built on. These people typically have deep experience building and managing large cloud infrastructure deployments, or leading reliability efforts for orgs similar to ours, or building release machinery to allow hundreds or thousands of devs to do their jobs without stepping on each others' toes. The systems and tooling where they may have experience depth may include (but not limited to): bazel, build tooling, cassandra, CDN, chef, configuration management, container orchestration, consul, docker, elasticsearch envoy, haproxy, kafka, kubernetes, load balancing, network architecture, postgres, redis, release management, RPC frameworks, service discovery, spinnaker, terraform, zookeeper. Bonus: You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. #LI-KM5 Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan. Th
Jobs in United States
Deployment Strategist in United States
636 active opportunities · Updated October 2026
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Explore current deployment strategist jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.
Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Field Service Specialist provides installation support, commissioning, maintenance, troubleshooting, and on-site customer support for deployed KARNO Power Modules. This is the first dedicated field service role supporting KARNO and is a foundational position within Hyliion's field service organization, which is being built to support installations across the United States. Early deployments focus on defense and data center applications. The position begins with an intensive training period of approximately three to four months in Milford, OH, working alongside the research, development, and engineering teams as KARNO units are built and serviced during final testing, including training on heat engine fundamentals, PLCs, HMIs, and advanced control systems. The position then transitions to field installation, commissioning, and long-term on-site support at customer locations, initially across the West Coast and expanding to other regions as the installed base grows. As the service organization scales, this position helps define its processes and standards. AI at Hyliion At Hyliion, AI is core to how we work. We equip every team member with leading AI tools and count on you to use them — to move faster, solve harder problems, and help us realize the full potential of KARNO technology for the world. Duties and Responsibilities Provide on-site maintenance, troubleshooting, and break-fix support for deployed KARNO units, with remote support from the engineering team. Diagnose issues using remote monitoring systems and troubleshooting logs. Troubleshoot controls, instrumentation, and high-voltage electrical system issues. Super
About the team OpenAI’s Forward Deployed Engineering team partners with banks, asset managers, insurers, and private capital firms to deploy production-grade AI systems in high-stakes financial environments. We operate at the intersection of customer delivery and core platform development, embedding deeply with customers to translate frontier model capabilities into reliable, auditable systems that create measurable business impact. Our work turns early deployments into repeatable solution patterns, operating standards, and evaluation practices that scale across regulated financial institutions. About the role We are hiring a Forward Deployed Engineer (FDE) to lead end-to-end deployments of OpenAI’s models inside financial services organizations where correctness, latency, explainability, and control matter. You will work with customers who are experts in investment banking, trading, risk, compliance, underwriting, research, operations, or investment decision-making, translating complex workflows, data constraints, and regulatory requirements into production systems. You will measure success through production adoption, workflow efficiency, risk reduction, revenue impact, and evaluation-driven feedback loops that inform product, model, and GTM strategy. You’ll work closely with Product, Research, GTM, Security, Legal, and GRC to deliver systems that meet enterprise standards for governance, auditability, and operational resilience. You will also play a central role in shaping OpenAI’s Financial Services offering — identifying high-value use cases, defining solution patterns, and building the first repeatable deployments that scale across institutions. Learn more about some of our work with financial institutions . This role is based in New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% may be required. In this role, you will Design and ship production AI systems around models, owning integrations,
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. Engineering Manager, Cloud Efficiency Snowflake runs large scale cloud infrastructure to deliver its own service — production and internal deployments, Kubernetes fleets, CI/CD, etc. Our cloud spend is in billions of dollars per year. We are looking for an experienced Engineering Manager to lead the Cloud Efficiency engineering team. In this role, you will own the technical vision and execution for building a unified, self-serve cloud efficiency platform along with AI skills and agents that makes resource usage and spend attributable and governable while driving insights and optimization of our cloud spend. AS AN ENGINEERING MANAGER IN CLOUD EFFICIENCY, YOU WILL: Lead and grow our talented team of software engineers, fostering a culture of technical excellence, ownership, and continuous learning. Drive the roadmap for Cloud Efficiency — translating company-level spend objectives into engineering systems: authoritative cost data, resource ownership registry, attribution pipelines, cost and unit economics modeling, observability, governance policies, and optimization workflows — in partnership with Product, Engineering, Finance, and Data Science. Set technical strategy for backend systems, data pipelines, and APIs that measure, attribute and surface cost and usage insights at
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: As a New Grad Software Engineer, you'll join a team of exceptional builders working on products that are reshaping how the world creates software. You'll have the opportunity to work on everything from our AI-powered development platform to the distributed systems that enable real-time collaboration for millions of developers. This is a chance to define your career while defining the future of software development. You'll work on problems that matter, with the autonomy to drive solutions and the support to grow into a technical leader. What you will build: Product features that delight users and make it possible for anybody to create software AI coding agent that understands intent and generates production-ready applications Cloud infrastructure that provides instant, powerful development environments at global scale Platform features that enable one click deployments and scale to millions of users Required skills and experience: Recent graduate (2027) with a degree in Computer Science, Computer Engineering, or related field Strong programming skills in a modern language (JavaScript/TypeScript, Python, Go, Rust) Full-stack capabilities with experience in React, Node.js, and database technologies Growth orientation - eager to learn new technologies and take on increasing responsibility Collaborative spirit - you work well in cross-functional teams and value diverse perspectives What we value : Problem-solving mindset: Ability to approach complex operational challenges systematically and devise effective solutions Self-directed and autonomous: Capable of working independently while collaborating effectively with cross-functional teams Strong communication skills: Ability to explain complex technical conce
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. Snowflake runs large scale cloud infrastructure to deliver its own service — production and internal deployments, Kubernetes fleets, CI/CD, etc. Our cloud spend is in billions of dollars per year. The Cloud Efficiency team builds a unified, self-serve cloud efficiency platform along with AI skills and agents that makes spend observable, attributable, governable while driving recommendations and optimization of our cloud spend. AS A SOFTWARE ENGINEER AT SNOWFLAKE YOU WILL: Design, develop, and maintain scalable platform for resource ownership registry, usage attribution, utilization measurement, and cost modeling. Build AI agents, tools and automation to enhance system monitoring, alerting, and root cause analysis. Improve and optimize data ingestion, storage, and query efficiency for cloud utilization, cost and efficiency data at scale. Collaborate with teams across Snowflake to understand attribution and observability needs and implement solutions that improve operational visibility. Contribute to open-source and industry best practices in monitoring and distributed systems monitoring. Ensure high availability, reliability, and performance of team-managed platforms by participating in on-call rotations and incident management. Partner with Finance, Product and Engineering
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. In this role you will: As a Hardware Test Engineer, you will work on Machine Learning/AI hardware system projects to craft the solutions for current and future data center deployments. You will bring a strong understanding of hardware system testing, excellent project management skills, and the ability to collaborate across multiple teams to ensure efficient lab operations. You will be responsible for designing, implementing, and executing comprehensive test plans that ensure the reliability, performance, and scalability of our supercomputing hardware systems. You will develop detailed test plans and methodologies tailored to hardware components, including processors, memory modules, custom accelerators and interconnects. You will collaborate with hardware design, manufacturing, firmware teams and vendors to identify, analyze, and resolve issues affecting hardware, power, thermal and high-speed interconnects. You will perform in-depth debugging on the hardware system Excellent analytical skills to diagnose hardware issues, troubleshoot problems, and propose solutions. Ability to interpret complex test data, identify trends, and draw meaningful conclusions. High-speed links, with a focus on SerDes (Serializer/Deserializer) technology to assess signal integrity, error rates, and overall link performance. You will collaborate with the lab manager to maintain the equipment and hardware systems, including oscilloscopes, thermal test chambers, liquid cooling systems, and other mea
From $104K/yr
MongoDB is hiring a Staff Product Marketing Manager to build and own our go-to-market narrative for the Public Sector vertical, with a focus on Federal Government and the broader public sector market. This is a foundational hire for MongoDB’s Industry Verticals product marketing function: you will define how MongoDB’s unified data platform, spanning cloud, on-premises, and hybrid database deployments with integrated, production-ready AI capabilities, shows up for government buyers. You’ll turn a major compliance milestone into a durable competitive differentiator: developing the positioning, messaging, and sales-ready content that helps government agencies, systems integrators, and cloud/public-sector resellers understand why MongoDB is the right data platform for mission-critical, regulated workloads. You do not need prior government or public-sector work experience to succeed in this role — you need to be an excellent product marketer who can get fluent in a new domain quickly and partner closely with the compliance, product, and sales experts who already are. This role can be based in one of our MongoDB hub offices in the U.S. or remotely in the U.S. What you’ll do Own positioning and messaging for MongoDB’s Public Sector go-to-market, leading the federal GTM and launch related activities Translate MongoDB’s data platform capabilities — document database, search, vector search, stream processing, and integrated AI — into mission-relevant outcomes and value propositions for government buyers and the systems integrators who serve them Partner with Compliance, Security, Industry Solutions and Product teams to accurately represent related certification requirements in external-facing content, staying current as MongoDB pursues additional authorizations (e.g., DoD Impact Levels) Build the public sector sales enablement toolkit: battlecards, pitch decks, discovery guides, ROI/value models, and competitive intelligence tailored to federal buying processes and procuremen
About the Team We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance. This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack. About the Role We’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident. A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT). You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack. This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most p
About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with research, software, and external hardware partners to shape the next generation of AI systems, from silicon through full-scale deployments. Our team focuses on understanding and optimizing performance across the full system stack—ensuring that architectural decisions are grounded in rigorous, quantitative analysis of real-world workloads. About the Role We are seeking a Performance Modeling Lead to build and lead a small, high-impact team responsible for answering forward-looking architectural questions across AI infrastructure systems. You will develop modeling frameworks and methodologies to evaluate system-level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long-term infrastructure strategy. This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance. 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. Key Responsibilities Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction. Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology. Develop performance models to guide decisions on: scale-up vs. scale-out architectures interconnect and network design memory hierarchy and system balance. Translate modeling outputs into clear recommendations for internal teams and external hardware vendors. Influence reference designs and vendor roadmaps through data-driven insights. Partner closely with machine learning, systems, and hardware teams to understand workload characte
WHAT IS BOX? Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift. WHY BOX NEEDS YOU The Solutions Engineering Team at Box includes solutions engineers, value engineering, platform solution engineering, enterprise architects, and demo engineering. As a Solutions Engineer, you are empowered to sell to business and IT leaders in every space and vertical, and take ownership in crafting customer-centric solutions. You will work alongside the account team to define and expand revenue opportunities, and ensure the solution is ready for cross company deployments. Y ou also act as a critical liaison between Sales and Product ; sharing customer feedback with the Product Management, Operations and Engineering functions at Box. Do you want to tinker, whiteboard, brainstorm and figure out how things work? Our highest perfo
Become a part of our caring community The Automation Engineer identifies and implements solutions (hardware and software) for improvement of the high-quality automation infrastructure. The Automation Engineer work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action. The Automation Engineer designs, programs, simulates, and tests automated processes, and is responsible for detailed design specifications and other documents. Understands department, segment, and organizational strategy and operating objectives, including their linkages to related areas. Makes decisions regarding own work methods, occasionally in ambiguous situations, and requires minimal direction and receives guidance where needed. Follows established guidelines/procedures. Use your skills to make an impact Required Qualifications Bachelor's degree or relevant and equivalent years of experience in lieu of degree requirement. 4+ years of technical experience related to automation. Strong knowledge and understanding of Claude code Experience using AI coding assistants such as Claude code, Github, Copilot, or similar developer productivity tools. Hands-on experience leveraging Claude Code for test automation development, debugging, script generation, and software quality engineering. Experience developing automation using Java, Python, or JavaScript. Experience with Selenium, Playwright, Cypress, or equivalent frameworks. Experience testing REST APIs and backend services. Experience with CI/CD pipelines and automated deployments. 2+ years of experience in Software QA testing in a SAFe Agile environment. Strong experience with black box, web-service integration and server back-end testing.</
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. About our Team: Micron’s Industrial and Physical AI team is driving the transformation of semiconductor manufacturing through Autonomous Operations, AI, robotics, and digital twin technologies! We develop and deploy innovative solutions across Micron’s global fabrication and assembly/test facilities, enabling smarter, safer, and more efficient operations at scale. Position Overview: We are seeking a hands-on Full-Stack AI Engineer to design, build, and deploy production-grade AI applications that support Micron's Autonomous Operations initiatives. This role owns the end-to-end development lifecycle, from data pipelines and AI models to APIs, web applications, digital twin integrations, and cloud/edge deployments, delivering impactful solutions for engineers, operators, and business leaders worldwide. Responsibilities: Design, architect, and deliver end-to-end AI products, including data ingestion pipelines, feature engineering, model training/inference, APIs, user interfaces, and application monitoring. Build and maintain modern front-end applications using React, Angular, or Streamlit, supported by backend services in Python and FastAPI. Develop scalable integrations between manufacturing systems, robotics platforms, AMRs, sensor networks, and enterprise applications to enable intelligent factory operations. Design and implement digital twin environments using platforms such as NVIDIA Omniverse, Gazebo, or Unity Robotics Hub to support simulation, validation, and o
JLL empowers you to shape a brighter way . Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. GROWTH ENABLEMENT DIRECTOR JLL Real Estate Due Diligence (JREDD) · Technical Services & Sustainable Operations What this job involves - JLL Real Estate Due Diligence (JREDD) is executing an ambitious multi-year growth strategy — scaling from a stabilized platform to a significantly larger technical services operation across facility condition assessment, environmental consulting, and data collection. The Growth Enablement Director leads JREDD's workforce delivery program — owning the interface between JREDD's multi-year workforce plan, JLL's internal Recruiting organization, and contracted external search partners. The role is responsible not just for filling requisitions, but for building the intake, onboarding, and ramp-to-productivity infrastructure that gets new hires billable faster and keeps first-year attrition low. JREDD’s hiring profile spans credentialed environmental and engineering professionals, high-volume field technicians, and program-driven international deployments — requiring the ability to operate across structured annual-plan recruiting and compressed, post-award demand cycles. This is a founding role. The Growth Enablement Director will stand up the function from scratch in Q4 2026, report to the JREDD Operations Manager, and oversee recruiting and onboarding execution ac
🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role AI research at WRITER isn't just about publishing papers — it's about building the scientific foundation that powers some of the most ambitious enterprise AI deployments in the world. As an AI research scientist, you'll be at the center of that work. You'll drive a high-impact research agenda focused on large language models, agentic reasoning, and the system-level capabilities that make AI genuinely useful at enterprise scale. This is a rare opportunity to do research that matters twice over — advancing the field and shipping directly into products used by hundreds of thousands of people every day. We're at an inflection point. Enterprises are moving from experimenting with AI to deeply embedding it across their operations, and WRITER's models are the engine making that possible. The work you do here — on post-training, planning, multi-step reasoning, and agentic workflows — will directly shape how the next generation of enterprise AI behaves, performs, and scales. You
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