Ai Platform Engineer Jobs

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

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 We are looking for an AI Agent Security Architect to function as the primary technical authority for Replit’s autonomous and AI agent security blueprint. In this critical role, you will design, implement, and maintain the runtime defense systems, guardrail frameworks, and sandboxing architectures that govern AI agents executing code, invoking tools, and reasoning across our platform. You will be a key technical contributor—leading high-impact AI security initiatives and bridging the gap between non-deterministic AI behavior and rigorous cybersecurity controls for both engineering and executive leadership. What You'll Do AI Agent Security Strategy & Technical Execution AI Agent Security Blueprint: Define the long-term vision and architectural patterns for securing autonomous agent workflows, Model Context Protocol (MCP) integrations, multi-turn reasoning loops, and multi-agent coordination. Runtime Guardrails & Policy Enforcement: Architect and deploy dynamic input/output guardrail systems, semantic firewalls, and real-time intent verification filters to prevent goal hijacking, system prompt leaks, and indirect prompt injections. Agent Execution & Tool Sandboxing: Partner with Infrastructure and AppSec teams to design secure, short-lived, micro-isolated environments (e.g., microVMs, WebAssembly, container sandboxes) where agents can dynamically execute code, run shell commands, and interact with host operating systems safely. Agentic Threat Modeling & Red Teaming: Conduct specialized threat modeling against non-deterministic systems. Lead automated and manual AI red-teaming initiatives to uncover vulnerabilities in RAG context pipelines, vector stores, and tool-calling interfaces. Identity

About the Team The Plugin Ecosystem team builds the platform and product experiences that let people extend ChatGPT and Codex. We work on plugins, skills, connectors, interactive apps, and open standards like the Model Context Protocol (MCP). We make plugins easy to discover, install, and use, ensure they’re invoked at the right time, and help people find new ways to get value from them. We want anyone to be able to turn a useful workflow into a plugin, share it, and have other people use it. A plugin can package instructions and skills with connections to the tools and data it needs. Our work spans creation and publishing, reliable execution across our products, clear permissions and approvals, and the controls admins need to bring plugins to their organizations. We work closely with research to improve plugin quality as models evolve. About the Role We’re looking for product-minded engineers to build the systems behind plugins and improve how models use them. Depending on your focus, you may scale generalist infrastructure and identity-related integrations across products, or improve plugin quality at the intersection of backend engineering and applied AI or work on the product experience itself to drive plugin usage. You’ll work across teams and own problems from diagnosis and design through implementation and release. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and ship APIs, SDKs, and services that developers use to extend ChatGPT and Codex. Build intuitive experiences that help users discover, install, and use plugins to get more done. Make plugins easier to create, test, publish, update, and share. Improve when and how models use plugins, from choosing the right plugin to completing a task. Work with Research to diagnose failures and measure improvements as models evolve. Improve plugin reliability and interaction quality acros

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. The AI Studio is the team responsible for designing, building, and operationalizing internal software platforms across every functional department of the company, including People Operations, Customer Support, Sales, Marketing, Finance, Recruiting, and Executive Operations. We treat each internal department as its own product surface, and in truth as its own startup, with its own customers, its own metrics, and its own reasons for existing. We ship custom software, built on Replit’s own platform, to solve operational problems that off-the-shelf SaaS tools cannot serve well at our scale and pace of growth. Position Summary The Member of Technical Staff (AI Builder) is a full-time builder role with substantial autonomy. You will design, architect, and ship AI-powered internal platforms that run the operations of the company across many departments at once. This is not a role for someone who wants a narrow, well-defined lane. It is a role for someone who wants to walk into an ambiguous business problem, understand it well enough to argue about it with the department lead, and then ship the software that fixes it. We are looking for people who genuinely understand the mechanics of a business: how revenue is actually made, why recruiting velocity matters, what makes support scale or break, how finance closes a month, and why each department is critical to whether the company wins or loses. You do not need to have run every function, but you need to respect why each one exists and be able to reason about it like an operator, not just an engineer. Because we treat each department as its own startup, we strongly favor people who have either run their own business or worked on a fast-scaling startup. You know what it feels like

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including AWS-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will Partner with strategic customers and in

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join the Pure Solutions team as a Senior MLOps Solutions Engineer to architect and build high-scale, enterprise-grade AI/ML solutions. You will be instrumental in integrating Pure Storage platforms with the evolving open-source MLOps ecosystem (Kubeflow, MLflow, Ray) to operationalize the complete machine learning lifecycle. This role requires a creative technologist with deep Python expertise to drive innovation and enable our customers and partners to achieve production AI success. WHAT YOU'LL DO Design and Automate MLOps Pipelines: Lead the development of end-to-end MLOps workflows using CI/CD tools (Git/Jenkins) and orchestration platforms (MLflow/Kubeflow), specifically integrating Pure Storage's FlashBlade, FlashArray, and Portworx as the high-performance data plane for data ingestion, training, and inference. Build High-Performance AI/ML Reference Architectures: Create validated, repeatable deployment models using Infrastructure as Code (e.g., Ansible, Terraform) for AI/ML environments spanning bare metal, virtual machines, and GPU-accelerated Kubernetes clusters, ensuring optimal performance for distributed training. Optimize and Operationalize GPU Inference: Architect and implement solutions for high-throughput, low-latency model serving, utilizing technologies like NVIDIA Triton Inference Server and advanced optimization techniques (quantization, model sharding like DeepSpeed/Megatron-LM, and dynamic bat

As a member of the AMER Solutions Org, you will act as a trusted advisor for prospects and clients, driving customer acquisition and accelerating revenue growth through a mastery of strategic sales and Asana platform expertise . In this role, you will be at the ground floor of an emerging go-to-market motion, partnering with a dedicated Account Executive to build repeatable technical plays for Asana Service Management across IT and service teams. You will bridge the gap between the voice of the business and the voice of the customer, gathering first-party insights to help shape how our product, demos, and technical positioning evolve . This role can either be fully remote or based in our New York City, San Francisco, or Chicago offices with an office-centric hybrid schedule . If based in-office: The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do and the teams with which you partner . If you're interviewing for this role, your recruiter will share more about the in-office requirements . What you’ll achieve Partner with the incubation Account Executive to lead technical validation for IT and service team opportunities within various customer segments and industries, managing everything from discovery to tailored product demonstrations and close. Translate complex customer pain points and service delivery workflows (such as request intake, triage, and fulfillment) into practical solution designs and compelling business value narratives for IT leaders. Advise customers on solution architecture, integrations, administration considerations, and deployment approaches to ensure a confident and seamless fit within their existing technology landscape. Collaborate cross-functionally with core Account Executives, Customer Success Managers, and core Solutions Engineers to uncover and support expansion opportunities within existing accounts. B

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the role: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement ro

We are looking for a deeply technical, customer-facing Forward Deployed Engineer to help product development organizations deploy Command - a new offering from Asana. As we incubate new motions and capabilities on Command, we need engineers who can work directly with customers, move quickly from insight to implementation, and bring real-world learning back into the product. This role is based in our San Francisco or New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Collaborate with Engineering leaders, platform teams, administrators, and hands-on builders to connect Command to the systems where work already happens Establish the technical and operational foundations for adoption and help teams develop more effective ways of planning, building, shipping, and learning Move between cloud infrastructure, integrations, workflow design, automation, product enablement, and engineering coaching Work directly in customer environments — configuring secure access to source-control, CI/CD, ticketing, and identity systems, or pairing with engineering teams to design release workflows and help leaders clarify the context their agents and teams need to make good decisions Write production-quality code when needed and turn customer-specific solutions into reusable product capabilities Leave customers with more than a working deployment — leave them with a stronger system for building software About you 6+ years of experience in software engineering, forward deployed engineering, customer engineering, solutions engineering, implementation engineering, or a similar technical customer-facing role Strong coding and systems-thi

We are looking for a deeply technical, customer-facing Forward Deployed Engineer to help product development organizations deploy Command - a new offering from Asana. As we incubate new motions and capabilities on Command, we need engineers who can work directly with customers, move quickly from insight to implementation, and bring real-world learning back into the product. This role is based in our San Francisco or New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Collaborate with Engineering leaders, platform teams, administrators, and hands-on builders to connect Command to the systems where work already happens Establish the technical and operational foundations for adoption and help teams develop more effective ways of planning, building, shipping, and learning Move between cloud infrastructure, integrations, workflow design, automation, product enablement, and engineering coaching Work directly in customer environments — configuring secure access to source-control, CI/CD, ticketing, and identity systems, or pairing with engineering teams to design release workflows and help leaders clarify the context their agents and teams need to make good decisions Write production-quality code when needed and turn customer-specific solutions into reusable product capabilities Leave customers with more than a working deployment — leave them with a stronger system for building software About you 6+ years of experience in software engineering, forward deployed engineering, customer engineering, solutions engineering, implementation engineering, or a similar technical customer-facing role Strong coding and systems-thi

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

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 Canada or can be based out of any of our Canada 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 to

About the Team OpenAI’s Applications Engineering organization builds and operates the products (such as ChatGPT & Codex) that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role We’re hiring Backend Software Engineers to design and implement safe services and infrastructure that power our core products. What You’ll Do Architect, build, and improve scalable backend systems and APIs. Drive performance, reliability, and safety across distributed services. Implement data storage, retrieval, compute, and integration solutions. Participate in long-term architectural planning and technical design reviews. Collaborate with cross-functional teams to design solutions that protect against and mitigate adversarial attacks without compromising user experience. You Might Thrive Here If You: Have strong experience with distributed systems, APIs, and backend languages (e.g., Go, Python, Rust, C++). Have experience setting up and maintaining production backend services and data pipelines. Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. Enjoy building resilient services that handle large scale and complexity. Are self-directed and enjoy figuring out the best way to solve a particular problem Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek

About the Team The ChatGPT Learning team focuses on building the next generation of learning experiences inside ChatGPT. Learning is already one of the largest consumer use cases on the platform, with millions of people each week using ChatGPT to understand concepts, practice skills, and get unstuck while learning. Our goal is to evolve ChatGPT from a place people go for one-off answers into a platform that helps people learn, grow, and make progress over time. We are exploring how AI can expand access to powerful learning tools for people everywhere—helping individuals better understand the world, build new skills, and pursue their goals. This team sits at the intersection of product engineering, design, AI research, and education, working to bring powerful learning experiences to a global audience. About the Role As a Full Stack Engineer on the ChatGPT Learning team, you will help design and build new product experiences that enable millions of people to learn with ChatGPT. You’ll work across the stack—from user-facing interfaces to backend services—to ship product features that make learning more intuitive, engaging, and effective. You’ll collaborate closely with researchers and platform teams to bring cutting-edge model capabilities into real-world products, helping translate advances in AI into experiences that people can use every day. We’re looking for engineers who enjoy building polished product experiences, operating with high ownership, and solving ambiguous problems that sit at the intersection of AI research and consumer software. This role is based in San Francisco or New York City. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. What You’ll Do Build end-to-end product experiences that help people learn with ChatGPT. Design and implement new multimodal capabilities that bring text, images, voice, and interactive interfaces into learning workflows. Develop scalable backend services and APIs t

Staff Software Engineer Bengaluru, Karnataka, India Opportunity Get Well is seeking a visionary and technically adept Staff Software Engineer to architect, design, develop, and optimize our cloud-native healthcare platform while driving the adoption of AI-First and AI-Augmented Software Engineering practices. This role is pivotal in shaping the future of software development at Get Well by combining deep technical expertise with modern AI-assisted engineering workflows. As we evolve toward an AI-First engineering organization, this leader will champion the use of Generative AI, AI development assistants, and Agentic AI to improve developer productivity, software quality, and engineering velocity. The ideal candidate brings deep expertise in software architecture, cloud-native application development, AI-enabled engineering, and distributed systems. This role provides technical leadership across multiple engineering teams, ensuring high standards for architecture, code quality, reliability, security, and AI adoption. This is a hands-on leadership role where strategic thinking meets deep engineering execution within a complex healthcare environment. This position reports to the Director, Product Development and requires close collaboration with software engineers, AI engineers, product managers, DevOps, QA, and compliance specialists. Key Responsibilities Technical Leadership Define and drive the architecture of scalable, distributed healthcare platforms. Champion AI-First Software Engineering practices across the development lifecycle. Lead the adoption of AI-Augmented Development , including spec-driven development, AI-assisted coding, code reviews, testing, and documentation. Establish engineering standards, Cursor/AI coding guidelines, reusable patterns, and governance for responsible AI usage. Provide hands-on leadership in architecture, coding, design reviews, debugging, and performance optimization. Mentor enginee