Technical Support Specialist in United States

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. As a Support Systems Lead at Replit, you'll build and own the systems that let support scale as fast as the product does. You'll own the tools our team works in every day, the technical setup behind self-service and AI-driven support, and the infrastructure that keeps all of it current as Replit ships. Replit is at the forefront of AI-driven software development, and how we support customers is constantly evolving. You'll shape how our support systems adapt to new products, new surfaces, and AI-assisted workflows, operating effectively in ambiguity and turning ad hoc fixes into infrastructure the whole team can rely on. You'll combine hands-on technical depth with systems thinking to keep builders moving, whether they get unblocked through self-service, an AI agent, or a person. This is an individual contributor role to start, with room to grow and build out a team as support scales. IN THIS ROLE YOU WILL: Configure and maintain Zendesk and the surrounding support stack, from the day-to-day workflow and automation setup to business rules and permissions, keeping it able to flex and scale as needs change. Build and maintain assignment logic, queues, tagging and taxonomy, and escalation paths, keeping them running cleanly as volume and workflows change. Set up and maintain support tooling, workflows, and access across internal agents, outsourced vendors, and regions, keeping the systems working for each group as the stack changes. Partner with Engineering on the technical requirements for self-service and in-product support surfaces, and build the entry points, help widgets, and routing behind them. Spot the repetitive steps in agent and admin workflows before they become bottlenecks, and build the automations, bulk acti

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. As a Support Systems Lead at Replit, you'll build and own the systems that let support scale as fast as the product does. You'll own the tools our team works in every day, the technical setup behind self-service and AI-driven support, and the infrastructure that keeps all of it current as Replit ships. Replit is at the forefront of AI-driven software development, and how we support customers is constantly evolving. You'll shape how our support systems adapt to new products, new surfaces, and AI-assisted workflows, operating effectively in ambiguity and turning ad hoc fixes into infrastructure the whole team can rely on. You'll combine hands-on technical depth with systems thinking to keep builders moving, whether they get unblocked through self-service, an AI agent, or a person. This is an individual contributor role to start, with room to grow and build out a team as support scales. IN THIS ROLE YOU WILL: Configure and maintain Zendesk and the surrounding support stack, from the day-to-day workflow and automation setup to business rules and permissions, keeping it able to flex and scale as needs change. Build and maintain assignment logic, queues, tagging and taxonomy, and escalation paths, keeping them running cleanly as volume and workflows change. Set up and maintain support tooling, workflows, and access across internal agents, outsourced vendors, and regions, keeping the systems working for each group as the stack changes. Partner with Engineering on the technical requirements for self-service and in-product support surfaces, and build the entry points, help widgets, and routing behind them. Spot the repetitive steps in agent and admin workflows before they become bottlenecks, and build the automations, bulk acti

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As an Assigned Support Engineer, you’ll be a trusted technical advisor to GitLab’s largest Self-managed, GitLab Dedicated, and GitLab.com customers, helping them avoid operational disruption and get the most from GitLab. You’ll combine deep Linux systems expertise, GitLab and CI/CD knowledge, and a proactive support mindset to understand each customer’s environment, anticipate and prevent issues, and solve complex technical and business challenges. In a typical week, you might be prioritizing strategic blockers with customer stakeholders, partnering with Product, Development, Infrastructure, Customer Succ

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our NYC or SF office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience in making ML systems performant at scale. If you are interested in contributing to open-source projects and Modal’s container runtime to push language and diffusion models towards higher throughput and lower latency, we’d love to hear from you! Requirements: 5+ years of experience writing high-quality, high-performance code. Experience working with torch, high-level ML frameworks, and inference engines (vLLM or TensorRT). Familiarity with Nvidia GPU architecture and CUDA. Experience with ML performance engineering (tell us a story about boosting GPU performance — debugging SM occupancy issues, rewriting an algorithm to be compute-bound, eliminating host overhead, etc). Nice-to-have: familiarity with low-level operating system foundations (Linux kernel, file systems, containers, etc).

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for strong backend engineers who love building a developer tools used by the largest AI companies in the world. You’ll be building for things at scale, but also for new AI workflows that change every day. Requirements: Experience building and shipping modern web applications end-to-end. We care more about what you’ve built than how many years you’ve been building. Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. Strong product instincts; yo

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We’re looking for strong engineers with experience building developer tools that users love to work with. Our ideal candidate is someone with a demonstrated drive to build beautiful interfaces that enhance developer productivity. Requirements: 5+ years of experience developing high-quality Python libraries with broad user-bases, ideally including some experience maintaining open-source software. Knowledge of advanced Python features, especially async programming. A strong product sense that manifests as a focus on developer ergonomics and productivity. A high level of customer empathy, good communication skills, and an openness to working directly with our users to help solve their problems. Ability to participate in on-call rotation and respond to production incidents. Ability to work in-person in our NYC or Stockholm office. Any of the following would be a plus:

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal. This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster. When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement. In this role you will:

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: Most of the value of owning a model shows up at serving time. We're building a platform that covers the whole life of an LLM -- train it, deploy it, observe it -- and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. What you'll do: Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spik

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. What you'll do: We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This role is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustnes

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role: Sentry is expanding our Technical Customer Success team to support our growing customer base and drive deeper adoption of the Sentry Platform worldwide. As a Technical Customer Success Manager (TCSM), you’ll be a Sentry product expert responsible for ensuring customers are successfully onboarded, achieve maximum value from our platform, and uncover new opportunities for growth through additional use cases and products. You’ll play a key role in helping customers realize measurable outcomes with Sentry. In this highly cross-functional role, you’ll collaborate closely with Account Executives (AEs), Sales Engineers (SEs), and Engineering teams to ensure customers’ technical and business goals are met. This role requires strong technical expertise and a deep understanding of the Software Development Life Cycle (SDLC) and related technologies. If you’re a technologist with experience supporting technical products in customer-facing roles—and you’re eager to join a fast-growing team delivering real value through an exceptional product—we’d love to meet you. In this role you will: Become a Sentry product expert and support customers by understanding their needs and helping them achieve their goals using the Sentry Platform. Drive customer success and health through effective onboarding, adoption, value realization, and retention. Collaborate with customer key stakeholders to define business and technical objectives, and work with the customer team to achieve them. Act as a trusted, strategic advisor to each assigned customer—driving best practices, innovation, and long-term success. Partner closely with the sales te

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. Our Talent team is looking for an experienced and discerning technical recruiter to help build Linear’s next generation of engineering talent. This is a hands-on, high-impact role for someone who sees recruiting as a craft. Your primary focus will be growing our engineering team in North America. You’ll work closely with engineering leadership and our existing recruiters across product, infrastructure, AI, mobile, and emerging technical roles. You’ll own the full search, from mapping talent markets and activating networks through assessment, work trial support, and close. Linear engineers tend to combine technical depth with product judgment, craftsmanship, and significant ownership. Finding them requires more than matching resumes to requirements. We’re looking for someone who can recognize these qualities, reach candidates with precision, and continually sharpen their judgment through close partnership with our team. All recruiters at Linear are generalists and may support other functions as company priorities evolve, but engineering will be the primary focus of this role. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in North American (Eastern time zone), with a strong preference for the New York City area. Being in New York enables closer partnership with our growing local team, c

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. At Roblox, we are growing and looking for a Technical Sourcer (short-term) to help build, scale, and influence our recruiting landscape. We are a fun and collaborative team focused on recruiting engineering talent. This person is a strong communicator, collaborator, and leads by example. Successful Builders embrace change and we encourage bringing in fresh ideas and a culture of feedback. You will directly impact the growth of the company and support our scaling efforts. The role is 6-12 month, with extensions possible depending on performance and business needs. We follow a hybrid schedule out of our San Mateo office, requiring in-office presence Tuesday–Thursday. You Will: Partner closely with Roblox recruiters and business leaders to deeply understand each team’s goals and talent needs, then identify, attract, and engage top candidates who will drive our mission forward Proactively source and engage top talent through Gem, LinkedIn Recruiter, SeekOut, and other platforms Influence and improve processes to help the team work smarter, faster, and at scale Share talent market insights with hiring managers to guide decisions on leveling, compensation, and candidate profiles Mentor and coach

We are Datadog’s in-house technical leaders. The Technical Account Management team drives Datadog’s continued global growth by ensuring our customers realize long-term value from our platform through successful adoption, expansion, and partnership. As a Manager 1 in Technical Account Management, you will lead and develop high-performing technical teams while influencing strategy, execution, and outcomes across customers, internal partners, and the broader organization. Manager 1 leaders at Datadog are people-first managers, trusted collaborators, and operational owners. You will coach and mentor individual contributors, drive execution against team and organizational goals, and serve as a strong voice for customer needs and technical excellence. 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: Lead and coach a team of up to 6 Technical Account Managers, providing regular 1:1s, team meetings, and bi-annual performance feedback Own and track team KPIs , including scheduling, utilization, productivity, and delivery outcomes Partner closely with Sales, Customer Success, Presales, Product Management, Support, and Marketing to align post-sales strategy and execution Lead and participate in customer-facing engagements when appropriate, including escalations, strategic reviews, and key account discussions Drive account strategy discussions focused on product adoption, expansion, and services delivery Actively participate in recruiting , hiring, and onboarding efforts across your team and the broader organization Gather and synthesize customer feedback to influence product direction, process improvements, and internal initiatives Lead multiple OKR initiatives annually , coordinating and delegating efforts across your team Demonstrate thought leadership by identifyi