Platform Deployment Management Lead Jobs

About the team OpenAI’s mission is to ensure artificial general intelligence (AGI) benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one organization. In pursuit of this mission, our Go-To-Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team includes Sales, Solutions, Support, Marketing, and Partnerships professionals who work together to create valuable solutions that help bring AI to as many users as possible. About the role OpenAI is seeking a highly motivated and experienced Account Director to join our Startup Go-To-Market team. You will play a critical role in owning relationships with top startup customers and supporting them in successfully building on the OpenAI platform. Many of the most disruptive and category-defining AI applications are being created by startups. The Startup Go-To-Market team's mission is to help startups harness the power of OpenAI’s technology to drive these advances. You will support startups in building effectively with OpenAI’s APIs, SDKs, and applications while providing access to OpenAI’s technical expertise and networks to help accelerate their progress. This role is a mixture of technical understanding, vision, partnership, and strategy. You’ll be responsible for serving as the primary relationship owner for a range of strategically important startup customers. You’ll also work cross-functionally with product, research, engineering, support, and technical solutions teams to help customers get the most out of our models. This role will be based in Tokyo . In this role, you'll: Manage a portfolio of startup accounts, developing and executing strategies for comprehensive account management. Partner with AI Deployment Engineers to drive successful technical engagements with startups. Own consumption and contracted revenue targets while managing revenue fo

About the team OpenAI’s mission is to ensure artificial general intelligence (AGI) benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one organization. In pursuit of this mission, our Go-To-Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team includes Sales, Solutions, Support, Marketing, and Partnerships professionals who work together to create valuable solutions that help bring AI to as many users as possible. About the role OpenAI is seeking a highly motivated and experienced Account Director to join our Startup Go-To-Market team. You will play a critical role in owning relationships with top startup customers and supporting them in successfully building on the OpenAI platform. Many of the most disruptive and category-defining AI applications are being created by startups. The Startup Go-To-Market team's mission is to help startups harness the power of OpenAI’s technology to drive these advances. You will support startups in building effectively with OpenAI’s APIs, SDKs, and applications while providing access to OpenAI’s technical expertise and networks to help accelerate their progress. This role is a mixture of technical understanding, vision, partnership, and strategy. You’ll be responsible for serving as the primary relationship owner for a range of strategically important startup customers. You’ll also work cross-functionally with product, research, engineering, support, and technical solutions teams to help customers get the most out of our models. This role will be based in Singapore . We use a hybrid work model of 3 days in the office per week. In this role, you'll: Manage a portfolio of startup accounts, developing and executing strategies for comprehensive account management. Partner with AI Deployment Engineers to drive successful technical engagements with startups. Own con

The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Staff Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and build production-grade AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, while making clear tradeoffs across prompting, fine-tuning, architecture, evaluation, and deployment. You will also partner closely with product, design, and engineering stakeholders to frame the right problems and communicate technical decisions clearly. This role is based in our New York office. What this looks like day-to-day Applied AI systems: Design and build AI-native systems, including RAG pipelines, agentic workflows, and LLM-powered product features. You will take ideas from prototype through production and ensure they can support real users. Model strategy: Make principled decisions about when to prompt, when to fine-tune, and when to use a different technical approach entirely. You will explain those tradeoffs clearly to engineers and non-engineers. Evaluation and guardrails: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and identifying hallucinations early. You will implement guardrails that hold up under real-world usage and load. Productionize AI ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will ensure AI systems are observable, performant, and production-ready. Full-stack delivery: Contribute across the stack when needed to get

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. We are looking for a Senior Automation Engineer to design and scale intelligent automation across Okta’s Enterprise Technology ecosystem. This role will reduce manual operational work, improve developer productivity, and accelerate the software delivery lifecycle across platforms such as Salesforce, NetSuite, AEM, Boomi, identity systems, CI/CD platforms, and other enterprise applications. The engineer will build reliable automation services, reusable integration patterns, and AI-assisted developer agents that understand source code, metadata, configuration, tickets, documentation, deployment history, and operational context. These solutions will automate release activities, identify deployment risks, reduce merge-conflict resolution effort, improve environment management, and enable safe self-service operations. The role requires a combination of software engineering, enterprise application expertise, API and integration development, CI/CD automation, security engineering, and practical experience applying AI to developer and operational workflows. The ideal candidate is comfortable moving between platform-specific technologies and building scalable, secure, platform-agnostic automation frameworks. What you'll be doing Intelligent Automation and Developer Productivity Build AI-assisted developer agents and automation services that reduce repetitive engineering and operational work. Use contextual information from Git repos

Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Design state-of-the-art ML models and large-scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints. Design systems to speed up the time from idea to deployment of new models. Experiment and iterate on ML models (using tools including PyTorch and TensorFlow) to achieve key business goals and drive efficiency. Develop pipelines and automated processes to train and evaluate models in offline and online environments. Integrate ML models into production systems and ensure their scalability and reliability. Collaborate with product and strategy partners to propose, prioritize, and implement new product features. Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus two (2) years of experience in Building and shipping ML systems in production. Must have two (2) years of experience in each of the following: ML algorithms and model architectures; Designing, training and evaluating machine learning models; Productionizing and deploying machine learning models at scale; Orchestrating data pipelines and leveraging large-s

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 seeking a Security Engineer to join our First-Party Hardware team. In this role, you will own the end-to-end security foundation for OpenAI's first-party AI hardware systems, working across hardware security, embedded security, system security, and practical deployment at data center scale. You will partner with silicon, hardware, firmware, infrastructure, manufacturing, operations, and security teams to define and deliver system-level device trust. This includes boot integrity, device identity, provisioning, attestation, management-plane security, storage encryption, debug controls, firmware update and recovery, RMA, and decommissioning. You will be accountable for turning threat models into requirements, requirements into implementation, and implementation into validation evidence that can support launch decisions. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you will: Own security requirements, threat models, validation strategy, and launch-readiness evidence for first-party hardware platforms from early design through production deployment. Design and review secure boot, measured boot, roots of trust, platform firmware resilience, firmware signing, recovery, and anti-rollback strategies across heterogeneous devices. Own device identity, provisioning, enrollment, attestation, certificate lifecycle, and key-management requirements across manufacturing and data center bring-up. Harden management

About the team OpenAI’s mission is to ensure artificial general intelligence (AGI) benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one organization. In pursuit of this mission, our Go-To-Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team includes Sales, Solutions, Support, Marketing, and Partnerships professionals who work together to create valuable solutions that help bring AI to as many users as possible. About the role OpenAI is seeking a highly motivated and experienced Account Director to join our Startup Go-To-Market team. You will play a critical role in owning relationships with top startup customers and supporting them in successfully building on the OpenAI platform. Many of the most disruptive and category-defining AI applications are being created by startups. The Startup Go-To-Market team's mission is to help startups harness the power of OpenAI’s technology to drive these advances. You will support startups in building effectively with OpenAI’s APIs, SDKs, and applications while providing access to OpenAI’s technical expertise and networks to help accelerate their progress. This role is a mixture of technical understanding, vision, partnership, and strategy. You’ll be responsible for serving as the primary relationship owner for a range of strategically important startup customers. You’ll also work cross-functionally with product, research, engineering, support, and technical solutions teams to help customers get the most out of our models. This role will be based in Sydney . In this role, you'll: Manage a portfolio of startup accounts, developing and executing strategies for comprehensive account management. Partner with AI Deployment Engineers to drive successful technical engagements with startups. Own consumption and contracted revenue targets while managing revenue f

NetSuite Developer The NetSuite Developer is responsible for the configuration and implementation of the brand-new NetSuite ERP solution based on business requirements and existing operational models. The ideal candidate will be responsible for configuration, programming and/or implementing as well as administering NetSuite application. Responsibilities Include: Assist with full NetSuite implementations as well as maintaining customer that have been using NetSuite Conduct data migrations from the current platform onto NetSuite. Collect requirements from clients for customizations/automation/integration Develop, test, and implement customized solutions for the NetSuite platform including scripts, workflows, and other customizations Create custom scripts using Suite Script 2.1 Communicate efficiently with functional consultants, project managers, and end-users Create custom forms, fields, searches, reports Install required bundles and 3rd party solutions Develop integrations with 3rd party systems with their APIs Conduct Testing Basic Qualifications: Previous experience working with NetSuite ERP and OneWorld is mandatory Experience creating custom scripts with Suite Script 2.0 & 2.1 2 years experience in JavaScript and other web programming languages 1-2 years of experience with Celigo Smart Connectors and Integrator.io Experience with configuration, sdf deployment and netsuite development Experience with advance pdf templates like check templates. NetSuite Suite Cloud Developer Certification is a plus Desired Qualifications: Experience in HTML, CSS3, JavaScript, jQuery, Backbone, Angular, AJAX, Suite Script Understanding of object-oriented concepts, abstraction/inheritance, as well as experience with object-oriented languages Data management preferred (SQL, XML, JSON) Web services preferred (REST, SOAP) How You’ll Embody Our Core Values At Plative, our core values shape how we work, collaborate, and grow. As part of the team, you will: Put Pe

About the Role REMOTE IN INDIA We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the work. You'll also build the systems that keep the fleet efficient, not just running, including defragmentation and rebalancing logic that consolidates scattered workloads back into contiguous capacity, and scheduling/bin-packing improvements that push GPU utilization up without hurting latency. The core value we're after is decoupling the people building on top of the platform from the operational and runtime complexity underneath, while squeezing more usable capacity out of the same hardware. You'll build the controllers, reconciliation loops, and self-service surface (API/CLI, not tickets) that make that decoupling real, plus the event-driven health, remediation, and utilization systems that keep it running and efficient without a human in the loop. Strong candidates have hands-on experience with Kubernetes controller/CRD patterns, have built or operated a platform API that abstracts multiple backends behind one interface, understand GPU scheduling and capacity efficiency (fragmentation, bin-packing, right-sizing), and think about GPU infrastructure as software to be engineered. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine

SDLC Engineer A Career with Point72’s Technology Team As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open-source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. What You’ll Do Provide expert technical support for our enterprise Software Development Life Cycle (SDLC) platforms including Jenkins, GitHub, Bitbucket, and AWS-based CI/CD pipelines Support and optimize our artifact management solutions (Artifactory) and static code analysis tools (SonarQube) Partner directly with business teams and development clients to address SDLC platform challenges and deliver effective solutions Implement and maintain security controls across our development toolchain and infrastructure Develop automation solutions to eliminate toil and enhance developer productivity Troubleshoot complex build, deployment, and integration issues across our development environments Contribute to continuous improvement of our AWS-based development infrastructure Maintain documentation and knowledge base for supported platforms and tools What’s required 5+ years of experience in software engineering, DevOps, or SRE roles Strong technical expertise in AWS services and cloud-native architectures Experience with container technologies (Docker, ECS, EKS) and container orchestration Deep understanding of Git workflows, branching strategies, and version control best practices Strong hands-on programming/scripting skills (Python, Go, or similar), with ability to debug and build automation for CI/CD pipelines Experience with infrastructure as code (Terraform, CloudFormation) in AWS environments Hands-on experience with CICD solutio

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a Data Engineer II to help us build the next generation of products which will go beyond just ID and enable our members to leverage the power of a networked digital identity. As a Data Engineer at CLEAR, you will participate in the design, implementation, testing, and deployment of applications to build and enhance our platform- one that interconnects dozens of attributes and qualifications while keeping member privacy and security at the core. A brief highlight of our tech stack: SQL / Python / Looker / Snowflake / dbt What you'll do: Build a scalable data system in which Analysts and Engineers can self-service changes in an automated, tested, secure, and high-quality manner Build processes supporting data transformation, data structures, metadata, dependency and workload management Develop and maintain data pipelines to collect, clean, and transform data (owning end to end data product from ingestion to visualization) Develop and implement data analytics models Partner with product and other stakeholders to uncover requirements, to innovate, and to solve complex problems Have a strong sense of ownership, responsible for architectural decision-making and striving for continuous improvement in technology and processes at CLEAR What you're great at: 4+ years of data engineering experience Working with cloud-based application development, and be fluent in at least a few of: Cloud services providers like AWS Data pipeline orchestration tools like Airflow, Dagster, Luigi, etc Big data tools like Spark, Ka

Opportunity Overview: We’re looking for a senior-level automation engineer who will help raise the bar on release quality, environment reliability, and change safety across Cohere’s platform. You’ll partner closely with Product, Engineering, Platform, and SRE to build scalable automation, guardrails, and validation systems that reduce production risk while increasing delivery velocity. This is not a “test scripts only” role. You’ll shape automation strategy, embed quality into the SDLC, and help define how changes move safely from dev → staging → UAT → prod in a fast-moving healthcare platform. You’ll help define how quality scales as Cohere grows. This role has real influence over release safety, platform reliability, and how engineering teams ship software in a regulated, high-impact domain. You won’t just test features — you’ll shape how Cohere delivers them safely to production. What you’ll do: Own and evolve Cohere’s end-to-end test automation strategy across UI, API, config changes, and critical workflows Design and maintain scalable E2E automation frameworks for multi-tenant, payer-specific workflows Build automated validation for deployment guardrails, release readiness, and production change safety Partner with Platform/DevOps to integrate automation into CI/CD pipelines and deployment workflows Create automated coverage for high-risk paths (authorization flows, partner integrations, file pipelines, feature flags, config changes) Drive test reliability, flake reduction, and actionable failure signals Define and enforce quality gates for prod releases, blue/green and canary deployments, and config changes Collaborate with Product and Engineering to ensure business outcomes are testable, measurable, and observable Improve test data management and environment stability to enable reliable automation at scale Mentor engineers on testability, automation best practices, and quality-first development Partner with SRE and Security to ensure production readines

Opportunity Overview: We’re looking for a senior-level automation engineer who will help raise the bar on release quality, environment reliability, and change safety across Cohere’s platform. You’ll partner closely with Product, Engineering, Platform, and SRE to build scalable automation, guardrails, and validation systems that reduce production risk while increasing delivery velocity. This is not a “test scripts only” role. You’ll shape automation strategy, embed quality into the SDLC, and help define how changes move safely from dev → staging → UAT → prod in a fast-moving healthcare platform. You’ll help define how quality scales as Cohere grows. This role has real influence over release safety, platform reliability, and how engineering teams ship software in a regulated, high-impact domain. You won’t just test features — you’ll shape how Cohere delivers them safely to production. What you’ll do: Own and evolve Cohere’s end-to-end test automation strategy across UI, API, config changes, and critical workflows Design and maintain scalable E2E automation frameworks for multi-tenant, payer-specific workflows Build automated validation for deployment guardrails, release readiness, and production change safety Partner with Platform/DevOps to integrate automation into CI/CD pipelines and deployment workflows Create automated coverage for high-risk paths (authorization flows, partner integrations, file pipelines, feature flags, config changes) Drive test reliability, flake reduction, and actionable failure signals Define and enforce quality gates for prod releases, blue/green and canary deployments, and config changes Collaborate with Product and Engineering to ensure business outcomes are testable, measurable, and observable Improve test data management and environment stability to enable reliable automation at scale Mentor engineers on testability, automation best practices, and quality-first development Partner with SRE and Security to ensure production readines

Opportunity Overview: We’re looking for a senior-level automation engineer who will help raise the bar on release quality, environment reliability, and change safety across Cohere’s platform. You’ll partner closely with Product, Engineering, Platform, and SRE to build scalable automation, guardrails, and validation systems that reduce production risk while increasing delivery velocity. This is not a “test scripts only” role. You’ll shape automation strategy, embed quality into the SDLC, and help define how changes move safely from dev → staging → UAT → prod in a fast-moving healthcare platform. You’ll help define how quality scales as Cohere grows. This role has real influence over release safety, platform reliability, and how engineering teams ship software in a regulated, high-impact domain. You won’t just test features — you’ll shape how Cohere delivers them safely to production. What you’ll do: Own and evolve Cohere’s end-to-end test automation strategy across UI, API, config changes, and critical workflows Design and maintain scalable E2E automation frameworks for multi-tenant, payer-specific workflows Build automated validation for deployment guardrails, release readiness, and production change safety Partner with Platform/DevOps to integrate automation into CI/CD pipelines and deployment workflows Create automated coverage for high-risk paths (authorization flows, partner integrations, file pipelines, feature flags, config changes) Drive test reliability, flake reduction, and actionable failure signals Define and enforce quality gates for prod releases, blue/green and canary deployments, and config changes Collaborate with Product and Engineering to ensure business outcomes are testable, measurable, and observable Improve test data management and environment stability to enable reliable automation at scale Mentor engineers on testability, automation best practices, and quality-first development Partner with SRE and Security to ensure production readines

The Team + The Role Our Emerging Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike. This role is based in our New York office. What this looks like day-to-day Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments. Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality. Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement guardrails that can withstand real-world load and production use. Productionize AI ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will help ensure AI systems are observable, efficient, and dependable in production. Full-stack product shipping: Contribute across the stack when needed because this team ships products, not just models