Software Engineer Product Security Data Platforms Jobs

Platform administration isn't the part of the product anyone screenshots for a demo. Nobody's writing a blog post about your identity provisioning flow. But it's the thing every other team at Diligent quietly depends on more than any other dev team in the company and when it breaks, everyone notices immediately. If that kind of quiet, high-stakes ownership sounds appealing rather than thankless, keep reading. This role is for someone who wants real skin in the game: you build it, you ship it, you support it. We're a high-initiative team that improves things we see first and asks permission later, building secure, event-driven microservices in TypeScript on AWS, and treating infrastructure as code the same way we treat application code: with rigor, not as an afterthought. Here's a breakdown of what you'll do (not all of it, just the important stuff) Design and build secure, scalable full-stack services using AWS serverless tech (Lambda, SQS, API Gateway) — with real attention to event-driven patterns and observability, not just "does it work on my machine." Own your services in production. That means building good observability, keeping an eye on alerts, and responding to them before they become bigger problems. Build infrastructure as code with AWS CDK and push for CI/CD that ships safely and often — not "big bang" releases you have to pray over. Design RESTful APIs other teams will actually want to consume: clear contracts, sane versioning, no surprises. Write tests — unit, integration, end-to-end — as part of how you build, not a chore you do after. Show up to architecture discussions with opinions and documentation, not just vibes. Use AI tools to move faster on coding, debugging, testing, and research — but you're still the one who validates the output. These are the essentials you'll need to get an interview 2-3 years of professional software engineering experience in an agile, full-stack-focused environment. Solid full-stack fundamentals: request lifecycles, d

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Software Engineer, you will own the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Design and implement scalable backend systems for Federal customers using cloud-native AI infrastructure. Build features for agentic systems including multi-layered guardrails and data retrieval optimization. Develop data pipelines and machine learning infrastructure to make data sources accessible by agents. Collaborate with cross-functional teams to execute backend solutions for secure environments. Participate in customer engagements to understand requirements and deliver technical solutions. Define requirements with stakeholders and implement features until they are accepted. Contribute to the platform roadmap and product strategy for the Federal business. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes

About the Team The Youth Well-Being product team is part of the Integrity pillar at OpenAI, responsible for ensuring that our state-of-the-art AI technologies are deployed in safe, age-appropriate, and beneficial ways—especially for youth and families. We work across OpenAI’s entire product surface area, from ChatGPT to future-facing tools, to architect safety and trust into the foundation of our systems. Our mission: empower families while meeting the highest standards of regulatory compliance and ethical responsibility. This work is core to OpenAI’s mission to ensure AGI benefits all of humanity. Safety, especially for the most vulnerable users, is more important to us than unfettered growth. About the Role We’re looking for a Senior Software Engineer to help architect and build the foundational systems that power family- and youth-facing experiences at scale. You’ll help define how teens and guardians engage with OpenAI products—ensuring those experiences are safe, compliant, and empowering. You’ll operate across a broad technical surface: building identity primitives, age assurance pipelines, and guardian tools that support both proactive and reactive interventions. You’ll collaborate closely with a cross-functional team of engineers, data scientists, designers, user researchers, and policy experts. This is a high-impact, 0→1 opportunity to set the standard for how families interact with generative AI. In this role, you will: Architect and implement teen and guardian experiences across OpenAI products, including ChatGPT. Build global age assurance systems that are privacy-preserving and tailored to regional compliance needs. Design and evolve our identity infrastructure to support scalable, secure, and resilient user journeys at consumer internet scale. Help define safety and well-being metrics, and continuously improve user trust through technical interventions. You might thrive in this role if you: Have built products or infrastructure for users under 18, or h

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role Build the most advanced AI Meeting Notes product — and expand it into broader “AI data capture” features that help teams turn conversations into durable context, tasks, and knowledge. Our mission is to 10x the rate of business context & data that enters Notion — optimized for agents — so teams get superhuman memory across workstreams and customers. Notion workspaces that use AI Meeting Notes already enter 6x more data on a daily basis, so we’re well on our way. What You'll Achieve Ship end-to-end product experiences across capture → transcript → summary → follow-ups (full-stack ownership). Make meeting & data capture feel effortless and magical (e.g., speaker identification via audio waveforms, richer in-meeting UX, smarter organization). Improve summary quality that teams trust: structure, factuality, and citations that make downstream agents and humans more capable. Raise the bar on reliability & observability across the pipeline (SLOs, debugging workflows, incident response) for realtime systems. Build agentic meeting workflows that turn discussions into tasks, follow-ups, and organized knowledge — so “w

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

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About The Role Data governance is one of the most critical challenges for Mixpanel's enterprise customers, and the AI era turns it into a foundational problem. Analytics and agents are only as trustworthy as the data beneath them. Poor data quality compounds: incorrect analyses spread as it becomes easier for anyone — or any agent — to query data, and the problem multiplies as customers scale into projects with high-cardinality events and fast-growing user bases. A data foundation that stays clean, consistent, and trusted is what sets Mixpanel apart. As a Senior Software Engineer on the Data Foundation team, you'll work across the stack to build high-impact features with extreme customer focus. You'll partner closely with engineers across the company, and with Design, Product, and GTM, to solve one of the hardest problems in analytics: keeping data clean, consistent, and trustworthy at scale. Curious what this looks like in practice? Read why data governance matters for AI-powered analytics on our blog. What You'll Do Build customer-facing features on our web application (React SPA) Collaborate closely with engineers and cross-functional partners across Product, Design, GTM, and beyond Take full ownership of projects — from shaping and delivery through iteration We're Looking For Someone Who Has Full-stack experience, with deep expertise in at least one of: Web application backends (Python, Django) High-volume APIs Search indexing A track record of leading projects end to end, not just executing tickets Comfort moving across the stack Bonus Points For Experience with data ingestion (Go) A data-driv

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. Who We Are: Shape the future of Roblox’s virtual economy. The Economy ML team is building the machine learning backbone that powers Roblox’s Marketplace, Developer Monetization, and Payments ecosystems. From intelligent pricing and personalized storefronts to dynamic layout optimization and avatar understanding, we’re reimagining how the Roblox economy drives user engagement, monetization, and creator success at scale. As a Principal Software Engineer (Data Systems) , you will architect, build and deploy high-scale, reliable real-time and batch data systems for personalization, search and recommendation across various product surfaces in Marketplace, Developer Monetization and Payments. You will be involved in key data projects from architecting event taxonomies and logging interfaces to real-time feature serving across multiple search and recommendation surfaces. What You’ll Do Act as data engineering lead for Economy ML, setting standards for batch vs streaming feature pipelines, table design, observability, and documentation used across the Economy group. Work as a hands-on contributor on our data systems to power content recommendation, search and personalization across Economy product

This role will join Datadog’s Data Visualization organization, a team responsible for the visualization experiences that power dashboards, notebooks, investigations, and product workflows used across the platform. The team is a highly product-oriented organization, building AI-native experiences that help customers understand, investigate, and interact with complex operational data. As a Staff Software Engineer, you will provide technical leadership in applying AI technologies to customer-facing product experiences, helping shape how users interact with Datadog through agents, conversational interfaces, and intelligent investigation workflows. You will partner across engineering and product teams to develop reliable, scalable, and trustworthy AI-powered experiences while helping establish AI engineering expertise within the broader organization. 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 the design and delivery of AI-powered product experiences across Datadog’s visualization and investigation surfaces. Develop systems that combine deterministic product capabilities with LLM-powered experiences to deliver trustworthy and explainable customer outcomes. Drive innovation in context engineering, prompt engineering, evaluation frameworks, and AI application reliability. Partner with product and engineering teams to improve investigation workflows and help customers discover insights more efficiently. Build experiences that enable Datadog capabilities to operate within third-party AI platforms, agents, and conversational environments. Provide technical leadership and mentorship while helping establish AI engineering best practices across the Data Visualization organization and broader Graphing group. Who You Are: You have extensive softw

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and contai

Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role can be based out of our New York City office or remotely within the United States and Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Po

Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role will be based remotely in Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Position Expectations Understand and improve the current funct

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

You’ll shape the future of a business‑critical platform as the technical lead across both product engineering and cloud infrastructure. You’ll modernize a mature .NET application running on AWS today, while steering its evolution toward a cloud‑native, React/Node.js, AI‑enabled architecture. If you enjoy owning architecture end‑to‑end, from backend and frontend through CI/CD, DevOps, and AWS infrastructure, this role gives you real influence at Staff Engineer level and the opportunity to set engineering standards that others follow. You’ll spend your time leading complex .NET and React features, designing scalable AWS infrastructure with Infrastructure as Code, and building automation that makes releases fast, safe, and repeatable. You’ll work on performance, reliability, and modernization in equal measure—fixing what’s slowing the platform down today and designing what it will look like in the next generation. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture and development of enterprise .NET services and APIs that power a business‑critical platform. Design and operate AWS infrastructure (using AWS CDK in TypeScript) to support secure, scalable, multi‑environment deployments. Build and optimize CI/CD pipelines (AWS CodePipeline, CodeBuild, Windows build agents) to make shipping .NET and React changes fast and reliable. Drive modernization initiatives across the stack, including clean architecture, refactoring legacy components, and reducing technical debt. Design and tune PostgreSQL and MSSQL database solutions for performance, scalability, and reliability. Mentor engineers and influence engineering practices across teams, raising the bar on cloud, DevOps, and software design. These are the essentials you’ll need to get an interview Significant experience (typically 8+ years) delivering and operating scalable enterprise software, owning both application code and cloud infrastructure. Deep hands‑on expertise with C

At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB). Our tools help teams deeply understand the humans behind their products, so they can build better ones. We are expanding our smart and driven team and would love for you to join us. Building AI-native products is a different problem than building deterministic software: the same input won't always produce the same output. Good product engineering here means designing experiences that stay useful, trustworthy, and easy to understand even when the AI underneath doesn't behave the same way twice — and knowing when that's a product design problem, not just a model problem. We're looking for a Software Engineer with 2-7 years of experience who thinks like a product owner, not just an implementer. You're comfortable being handed a vague, half-formed problem and figuring out what's actually worth building. You default to empathy for the researcher or participant on the other end of the screen, and you'd rather ship something real and learn from it than wait for a perfect spec. You're fluent enough with modern LLM-based systems to build good product experiences on top of them, even if tuning the model itself isn't your job. What you'll do Own end-to-end delivery of product features — from an ambiguous problem statement to shipped, working software real researchers and participants use Partner directly with Product and Design to help define what should be built, not just how to build it Use our design system to make sound, independent calls on smaller UX and interaction decisions, and know when a change is big enough to loop Design in Build the product surfaces (web app flows, dashboards, in-product controls) that make AI-driven behavior understand

About the Team The Monetization team is a cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across OpenAI’s ads products. This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Sc