Go To Market Engineer in United States

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as our next Backend Software Engine

We are Datadog's in-house product experts. The technical solutions team enables Datadog's worldwide growth by educating potential clients and ensuring that existing customers are happy and successful. The Partner Solution Architect (PSA) is a Datadog expert who will work closely with Datadog’s Director of Partner Solutions Architects, and is aligned to our Channels & Alliances business segment. The PSA is responsible for supporting a variety of technical initiatives and activities for our partners (for example: cloud migration, application modernization, DevOps transformation). They are accountable for the outcome of these initiatives, and frequently collaborate with both Datadog and Partner resources to drive success. The PSA is a trusted technical advisor for our Partner channel. 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: Ensure the successful onboarding, training, enablement, and certification of partner technical resources; Participate in periodic joint business planning and review sessions to ensure direct alignment between Datadog and Partner technical teams; Collaborate internally to support Partner technical initiatives such as end-customer demonstrations and proofs of value; partner team enablement workshops; assessment, advice, and coaching on lead practices; Advocate on behalf of Partners’ technical concerns (use cases, feature requests, support issues, e.g.) with Datadog internal teams and personnel, helping to bring those concerns to resolution; Analyze and understand Partner service offerings on a regular basis and provide recommendations to enhance the value of those services through greater or improved adoption of Datadog features and capabilities; Collaborate with Datadog’s product management, engineering and techn

The Code Gen team is tasked with building AI-powered code transformation tools that transform rigid, legacy applications that suffer from poor scalability and high operating costs into modern, microservices-based architectures that are built on top of MongoDB. Join our team and be at the forefront of innovation and creativity. We are looking for a Staff Engineer with domain expertise and years of experience in modernizing legacy applications that are based on traditional database systems. A significant advantage is profound prior experience in leveraging AI, particularly LLMs and GenAI capabilities, to enable reliable, self-driving automation of the code transformation, iterative build, and test processes. In this role, you will be instrumental in initiating technical strategies and ideas, lead the Code Gen team in designing, building, and optimizing our code transformation workflow and tools. You will work on critical components that ensure the scalability, efficiency, and reliability of our services. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation, build and test. This role will be based remotely in North America. A strong candidate for this position will have Extensive experience (8+ years) in software development and operations, with a proven track record of delivering high performance, correctness, and architectural excellence in fast-paced environments Experience using Relational Databases such as Oracle, MySQL, Microsoft SQL Server or PostgreSQL Experience with tools and methodologies for code analysis, refactoring, and automated testing Experience in designing and implementing complex software systems, collaborating effectively with engineers of all experience levels to achieve high reliability and performance Practical knowledge of integrating GenAI into large-scale, complex systems, including a clear unde

The Team Platform Engineering is the department within SRE that is responsible for a range of critical infrastructure and operational functions that support the broader engineering organization. Among these are our multi-cloud-provider Kubernetes infrastructure, deployment machinery, and observability and alerting systems. The Fabric team manages the infrastructure that enables secure communication between systems and from the public internet. Their responsibilities encompass network architecture, service mesh, and edge load balancing, ensuring customer data remains safe in transit. The team plays a crucial role in developing and maintaining the reliable and globally connected multi-cloud network that supports MongoDB products. This role can sit in our NYC HQ, our smaller Austin, Palo Alto, or San Francisco offices, or fully remote from anywhere in North America. When based in an office, we provide hybrid work accommodation. Role Overview We are seeking a talented Site Reliability Engineer (SRE) with a strong networking background to join the Fabric team. This role is pivotal in building and maintaining the robust infrastructure necessary for secure and efficient communication between our services. As an SRE on the Fabric team, you will leverage your expertise in networking, distributed systems, and automation to ensure our systems are resilient, scalable, and reliable. The ideal candidate should Have 10+ years of experience working on software and operating distributed systems, with deep expertise in networking fundamentals and a good understanding of how the internet works, e.g. TCP/IP (including IPv6), DNS, TLS/mTLS, BGP, tunnels, overlays, and SDN principles Possess a customer-focused mindset, driving improvements that benefit end-users Value efficiency in processes and operations, and display a strong preference for automation over manual processes (“allergic to ops work”) Be intimately familiar with modern cloud-based infrastructure and the network design prim

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's

About the Team The People Technology team builds and operates the systems that support how OpenAI hires, develops, and supports its people. The team brings together People Systems and People Innovation Labs, a product engineering group focused on rethinking how we find and retain exceptional talent and help employees do their best work. People Systems owns the company’s core people-technology ecosystem, including platforms such as Workday and Ashby. People Innovation Labs builds new employee and People Team experiences on top of that foundation, including OpenHouse, our internal employee hub, and AI-powered products and automations. Together, we are working toward a model in which our enterprise systems provide reliable data, controls, and core business logic, while employees and managers can complete more of their work through simple, integrated, and AI-native experiences. About the Role We are looking for a People Systems Lead to manage the People Systems team and shape how our core systems evolve. You will be responsible for the reliability and effectiveness of our current environment while helping us move beyond the constraints of traditional enterprise software. This includes stabilizing and improving platforms such as Workday and Ashby, designing the integrations that connect them to the broader technology ecosystem, and partnering with People Innovation Labs to surface workflows through OpenHouse, Slack, and AI-powered experiences. This role requires someone who is comfortable moving between strategy, technical design, and team leadership. You should understand People systems deeply, be able to work through integration and architecture decisions with engineers, and translate complex organizational needs into scalable solutions. You will also manage vendor relationships, develop the People Systems team, and drive alignment across People, Engineering, Finance, Security, Legal, and other partners. This role could be a fit for someone who has grown up in People S

About the Team OpenAI’s Network Engineering team within IT and Security advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient network services. We build and operate the connectivity that supports OpenAI’s offices, labs, campuses, cloud environments, people, and devices. By combining strong network fundamentals with security, reliability, automation, and user-centered design, we enable impactful AI research, corporate operations, and product innovation. About the Role As a Network Engineer at OpenAI, you will design, operate, and continuously improve the global networks that connect our offices, labs, campuses, PoPs, cloud environments, people, and devices. The role spans strategic platform engineering and responsive production operations: you will shape architecture, standards, roadmaps, lifecycle plans, and automation while supporting incidents, escalations, and time-sensitive delivery. Operational signals will inform what we stabilize, simplify, standardize, or automate next. We work backward from user needs, investigate root causes, own outcomes end-to-end, and move quickly without compromising security. We are looking for a versatile engineer who can make pragmatic reliability and security tradeoffs, communicate clearly, and turn recurring operational work into durable platforms, tooling, and standards. You will partner across IT, Security, AppEng, Research, Applied, workplace teams, carriers, and vendors. In this role, you will: Design, implement, and operate secure, scalable enterprise networks across offices, labs, campuses, PoPs, cloud connectivity, and hybrid environments. Set strategic direction for network services through architecture, standards, roadmaps, lifecycle planning, capacity strategy, and measurable reliability outcomes. Own production operations, including on-call, incident response, escalations, and time-sensitive delivery, while protecting user experience,

About the Team OpenAI’s Application Engineering team builds the internal products and platforms that help OpenAI operate securely and at scale. We engineer, own, and evolve OpenAI’s core productivity ecosystem, creating secure applications, integrations, automation, and reusable tooling where off-the-shelf software is not enough. Our work spans employee-facing experiences and the services, APIs, control planes, and governance that make them reliable, permission-aware, and scalable. We also act as a customer zero for OpenAI’s technology, building the enterprise foundations that let employees and agents safely access the context, tools, and actions they need. We partner closely with IT, Security, product teams, and platform providers to turn company-wide problems into durable systems, learn from real internal workflows, and help shape the products we deploy. We create paved paths that let teams move quickly without compromising security or operational quality. About the Role As a Staff Software Engineer on Agent Productivity, you will shape the foundation that enables teams to build agents with secure access to the context and capabilities they need. Slack will be the first and deepest implementation surface—and where you spend most of your time—owning its application architecture, integrations, APIs, governance, and administration automation while building patterns that extend to internal systems, identity platforms, and other enterprise applications. This is a hands-on engineering role with broad organizational impact as agents support more employee workflows. You will define platform architecture, build reusable foundations, and establish secure patterns for identity, permissions, connectivity, and operations that make agents easier to develop, deploy, and manage. In this role, you will: Own the technical strategy and architecture that enable teams to build, connect, and deploy agents quickly and safely, using Slack as the primary implementation surface. Design and

About the Team The Finance & Supply Chain Engineering organization includes two complementary teams. Software Engineering builds internal full-stack applications, durable agentic workflows, plugins, MCPs, and measurable AI-enabled engineering practices. Data Engineering builds trusted analytics data assets for Finance and Supply Chain. The teams have distinct charters, with important shared dependencies and broad cross team partnerships across Engineering, Applications, Finance, and Supply Chain. About the Role We are looking for a hands-on senior technical leader who will report alongside the Software Engineering and Data Engineering managers. This is an individual-contributor role with no immediate people-management responsibility. The Tech Lead will raise the technical bar across both teams, participate in important cross-team or high-risk design decisions, and directly own and ship high-impact work. The role should improve team judgment and autonomy rather than act as a floating architect or universal approval gate. In this role, you will: Partner with the Software Engineering and Data Engineering managers as a peer technical leader; managers retain accountability for people, staffing, priorities, performance, and delivery commitments. Directly own the architecture, implementation, launch, and operation of one or more high-impact initiatives, remaining accountable for real outcomes rather than advisory output alone. Guide important design decisions that are cross-team, difficult to reverse, or material to security, financial controls, reliability, data quality, or long-term cost of ownership. Establish pragmatic engineering standards across architecture, APIs and data contracts, testing, security, reliability, observability, lineage, data quality, and operational ownership. Advance engineering standards for building with AI, including agentic workflows, evaluation, telemetry, adoption, and outcome measurement. Work across backend, full-stack, data, and big-d

The ChatGPT Finances team builds experiences that help people connect their financial accounts, understand their financial picture, and ask useful questions about their finances through ChatGPT. Our work spans account connectivity, data ingestion, dashboards, personalized insights, and conversational experiences. We collaborate across product, design, research, infrastructure, security, and data integrations to make complex financial information understandable and actionable. This is an early and ambitious product area with a substantial roadmap. We are looking for engineers who want to shape both the first user experiences and the durable systems required to earn and keep users’ trust. About the role We’re looking for full-stack product engineers to build and scale ChatGPT Finances. You will own features across the stack—from polished frontend experiences to the APIs, services, and data models that power them. This role is well suited to engineers who combine strong product judgment with broad technical depth. You should care about how quickly users can understand their financial lives, how reliably data moves through the system, and how AI can answer financial questions in a grounded, transparent, and useful way. You will work closely with product, design, research, infrastructure, security, and data integration teams to take ideas from early prototypes to reliable production experiences. In this role, you will Own full-stack product features from user experience and frontend implementation through backend services, data models, deployment, and observability. Build polished, accessible, and performant interfaces for account connection, dashboards, insights, and conversational workflows. Design APIs and backend systems that safely ingest, normalize, and serve financial data. Build resilient integrations that handle synchronization, data freshness, partial failures, permissions, and user consent. Bring new AI capabilities into production while prioritizing grounding

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Controls Network Engineer, you will design, validate, and scale the controls and OT network architectures that support high-density AI data centers. You will work across controls systems, OT infrastructure, telemetry, commissioning, deployment, and operations, partnering with mechanical, electrical, IT/networking, security, and external delivery teams. About the Role We are seeking a mid to senior OT Network Engineer with a strong controls systems background to lead the design and operation of resilient, secure, and scalable OT network architectures for high-density AI data centers. This role translates compute, power, cooling, and operational requirements into practical OT network designs, evaluates vendor solutions, and drives technical decisions across controls infrastructure, telemetry, commissioning, and operations. The ideal candidate has strong hands-on experience in mission-critical OT environments, including industrial networking, virtualized infrastructure, and OT network operations, with expertise in routing, switching, segmentation, firewall policy, time synchronization, monitoring, and network lifecycle support. Key Responsibilities Define controls, automation, and OT network requirements for AI data center campuses. Develop reference architectures, engineering standards, and reusable design templates. Review and develop basis-of-design and functional design documents, including OT network diagrams, IP/VLAN schemes, telemetry architectures, data flow diagrams, and commissioning requirements. Design OT and infrastructure network architectures, including physical topology, logical topology, IP addressing, subnetting, VLA

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Electrical Engineer, you will help define, validate, and scale the electrical power systems that support high-density AI compute. You will translate evolving compute requirements into practical facility and rack-power architectures, evaluate new technologies and vendor solutions, and drive technical decisions across design, manufacturing validation, construction, commissioning, deployment, and operations. This role is best suited for a senior hands-on engineer with deep experience in mission-critical power systems, strong judgment under ambiguity, and the ability to connect facility infrastructure, hardware requirements, controls, telemetry, reliability, and operations. About the Role We are seeking a senior electrical infrastructure engineer to lead the development of reliable, scalable, and efficient power architectures for high-density, liquid-cooled AI data centers. The ideal candidate has strong practical experience with critical electrical systems at data centers or comparable industrial scale, including medium-voltage and low-voltage distribution, utility interfaces, backup power, UPS and battery systems, rack power delivery, grounding, protection, controls, and monitoring systems. You should be comfortable moving between long-range architecture, detailed engineering review, lab validation, vendor qualification, field deployment, and operational troubleshooting. Key Responsibilities Design and optimize electrical topologies and equipment strategies that reduce cost, accelerate schedules, improve efficiency, increase scalability, and maintain high reliability and maintainability. Review and develop basis-of-des

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

About the Team IT Systems Operations serves as the operational control layer connecting Security, Engineering, and Employee Technology platforms. The team ensures employee-facing systems, identity workflows, and enterprise applications operate in a predictable, governed, and continuously reliable manner as the organization scales. Beyond implementation, the team establishes structured operating patterns that ensure platform changes, access models, integrations, and lifecycle workflows evolve safely and consistently across the enterprise environment. About the Role This role acts as an operational owner for identity-connected enterprise SaaS platforms and system change controls supporting OpenAI’s compliance requirements. The engineer will be responsible for ensuring that production configuration, access models, and platform changes remain compliant, auditable, and consistently operated through defined controls. You will own and operationalize controlled system and workflow changes across identity platforms, SaaS applications, collaboration tooling, and enterprise infrastructure. You will partner closely with Security, Platform Engineering, and IT Support Operations to: Ensure identity and access workflows behave consistently across systems Implement structured rollout and configuration practices for enterprise applications Improve visibility and traceability of system changes impacting employee workflows Translate operational requirements into durable automation and policy-aligned implementations Success in this role requires not only strong engineering capability, but also sound operational judgment, disciplined documentation practices, and effective cross-functional collaboration. In this role, you will: Enterprise SaaS & Identity Platform Ownership Own administration and operational stewardship of enterprise SaaS and identity-connected platforms, ensuring configuration integrity, access governance, and compliance with defined control requirements. Own onboard