Area Business Manager Jobs

About the Team The Storage teams build and operate online stateful systems and abstractions that are reliable, efficient, secure and easy to use for DoorDash Engineering. The teams are responsible for understanding Product Engineering’s evolving needs and developing platform and infrastructure capabilities to serve them. The team currently supports CockroachDB, Cassandra, Kafka and Redis as well as data abstraction services to reduce the complexity of interacting with storage systems for Product Engineers. About the Role The Storage team is building and operating a high-performance, scalable, and reliable data abstraction layer that optimizes both efficiency and reliability. Our goal is to create a platform that manages itself and fades into the background—empowering engineers to focus on delivering product experiences our customers love. This role is available across two teams within Storage, each solving unique and high-impact challenges: One team is building the orchestration layer for DoorDash’s storage platform—unifying lifecycle management, operations, and self-serve APIs for databases and streaming systems, turning complex, stateful infrastructure into reliable, developer-friendly services used across the company. One team builds and operates the distributed data platform powering DoorDash's largest stateful workloads -- including Cassandra, which backs critical product surfaces across DoorDash, Wolt, and Roo. You'll design high-throughput data abstractions, smart clients, and platform services that make distributed data reliable and easy to work with at multi-petabyte, multi-million-QPS scale, with opportunities to go deep on distributed systems internals and contribute to the open-source Cassandra ecosystem. If you're passionate about distributed systems, developer experience, and building foundational infrastructure at scale, we'd love to hear from you. You must be located in San Francisco, Sunnyvale, Seattle, or the New York Metro Area for this hybrid pos

About the Team At DoorDash, design means making experiences for the people who order, the people who prepare, and the people who deliver. As a Design Manager at DoorDash, you want to build things that matter to real people. You're at your best when you can move from idea to shipped product quickly, bringing experiences to life that reach and influence users at massive scale. You'll care about whether the product you make solved a real problem for real people, or changed how someone experiences their day. You'll work shoulder-to-shoulder with Engineering and Product Management, dig into the data, and use LLM-powered tools alongside traditional design tools. If the LLM powered tools don’t exist yet, you build them. About the Role Trust is the foundation of every interaction on DoorDash. We're looking for a design leader who can define and drive a vision for designing for integrity at scale. In this role, you will join the Integrity organization. You’ll lead a team of designers working across fraud prevention, trust, safety, and compliance — protecting millions of consumers, Dashers, and merchants while keeping the platform seamless and trustworthy. You will report into the Head of Design for our Customer Experience & Integrity organization. This role is hybrid- 1–2 days per week in one of our Design Hubs. You’re excited about this opportunity because you will… Set the technical direction for Design across your product area — decide what gets built, in what order, and why; connect multiple teams around shared platforms so the work compounds instead of duplicating Work on ambiguous problems and turn them into architecture decisions and working systems that teams actually use; earn trust with leadership not through decks, but through prototypes and shipped code that make your point for you Stay close to the code and the craft across multiple projects at once — you're not just reviewing, you're building; the work you ship will move real metrics across the product area

About the Team The GSIO Workforce Management Planning Team consists of our Senior Manager, 3 Workforce Managers, multiple Workforce Planners/Schedulers and RTAs. Enjoy a comfortable team-oriented environment where things are always happening at a rapid pace and you can prioritize and organize tasks simultaneously. Manage outcomes and be empowered to make the decisions to lead to those outcomes. Be focused on quality, output-motivated, an extreme achiever who is progressive, and always pushing yourself to be 1% better each day! About the Role As one of DoorDash’s core operations teams, Support Ops is tasked with ensuring that when there are bumps in the last mile there’s always someone there to help make things right. Our team designs, manages and operates DoorDash’s massive and growing global network of support centers, with the ultimate goal of delivering a world-class customer experience every time. As part of DoorDash’s Support Operations Team, we’re looking for an experienced Workforce Planner to help develop and scale our support lines of businesses in the Mexico City area. This role will be a key player in planning our monthly, daily, and hourly staffing levels and ensure we’re providing our customers with best-in-class service with up to date hiring plans. This role will play a vital part in improving forecast accuracy, reporting, and planning around floor staff utilization and efficiency. You’re excited about this opportunity because you will… Build and maintain support capacity plan models at a monthly, weekly, and interval level for a large, 24/7/365 organization. Forecast incoming contacts based on Delivery volume, Mx and Dx onboarding. Analysis on historical data to provide insights that improve support operations. Guide Short-Term staffing adjustments to address current staffing gaps. Work with our operations team to track how our staffing is being implemented and optimized. Make proactive and corrected improvements. Partner with Real Time Analysts for

About the Team The GSIO Workforce Management Planning Team consists of our Senior Manager, 3 Workforce Managers, multiple Workforce Planners/Schedulers and RTAs. Enjoy a comfortable team-oriented environment where things are always happening at a rapid pace and you can prioritize and organize tasks simultaneously. Manage outcomes and be empowered to make the decisions to lead to those outcomes. Be focused on quality, output-motivated, an extreme achiever who is progressive, and always pushing yourself to be 1% better each day! About the Role As one of DoorDash’s core operations teams, Support Ops is tasked with ensuring that when there are bumps in the last mile there’s always someone there to help make things right. Our team designs, manages and operates DoorDash’s massive and growing global network of support centers, with the ultimate goal of delivering a world-class customer experience every time. As part of DoorDash’s Support Operations Team, we’re looking for an experienced Workforce Planner to help develop and scale our support lines of businesses in the Mexico City area. This role will be a key player in planning our monthly, daily, and hourly staffing levels and ensure we’re providing our customers with best-in-class service with up to date hiring plans. This role will play a vital part in improving forecast accuracy, reporting, and planning around floor staff utilization and efficiency. You’re excited about this opportunity because you will… Build and maintain support capacity plan models at a monthly, weekly, and interval level for a large, 24/7/365 organization. Forecast incoming contacts based on Delivery volume, Mx and Dx onboarding. Analysis on historical data to provide insights that improve support operations. Guide Short-Term staffing adjustments to address current staffing gaps. Work with our operations team to track how our staffing is being implemented and optimized. Make proactive and corrected improvements. Partner with Real Time Analysts for

About the Team The GSIO Workforce Management Planning Team consists of our Senior Manager, 3 Workforce Managers, multiple Workforce Planners/Schedulers and RTAs. Enjoy a comfortable team-oriented environment where things are always happening at a rapid pace and you can prioritize and organize tasks simultaneously. Manage outcomes and be empowered to make the decisions to lead to those outcomes. Be focused on quality, output-motivated, an extreme achiever who is progressive, and always pushing yourself to be 1% better each day! About the Role As one of DoorDash’s core operations teams, Support Ops is tasked with ensuring that when there are bumps in the last mile there’s always someone there to help make things right. Our team designs, manages and operates DoorDash’s massive and growing global network of support centers, with the ultimate goal of delivering a world-class customer experience every time. As part of DoorDash’s Support Operations Team, we’re looking for an experienced Workforce Planner to help develop and scale our support lines of businesses in the Mexico City area. This role will be a key player in planning our monthly, daily, and hourly staffing levels and ensure we’re providing our customers with best-in-class service with up to date hiring plans. This role will play a vital part in improving forecast accuracy, reporting, and planning around floor staff utilization and efficiency. You’re excited about this opportunity because you will… Build and maintain support capacity plan models at a monthly, weekly, and interval level for a large, 24/7/365 organization. Forecast incoming contacts based on Delivery volume, Mx and Dx onboarding. Analysis on historical data to provide insights that improve support operations. Guide Short-Term staffing adjustments to address current staffing gaps. Work with our operations team to track how our staffing is being implemented and optimized. Make proactive and corrected improvements. Partner with Real Time Analysts for

About the Team The GSIO Workforce Management Planning Team consists of our Senior Manager, 3 Workforce Managers, multiple Workforce Planners/Schedulers and RTAs. Enjoy a comfortable team-oriented environment where things are always happening at a rapid pace and you can prioritize and organize tasks simultaneously. Manage outcomes and be empowered to make the decisions to lead to those outcomes. Be focused on quality, output-motivated, an extreme achiever who is progressive, and always pushing yourself to be 1% better each day! About the Role As one of DoorDash’s core operations teams, Support Ops is tasked with ensuring that when there are bumps in the last mile there’s always someone there to help make things right. Our team designs, manages and operates DoorDash’s massive and growing global network of support centers, with the ultimate goal of delivering a world-class customer experience every time. As part of DoorDash’s Support Operations Team, we’re looking for an experienced Workforce Planner to help develop and scale our support lines of businesses in the Mexico City area. This role will be a key player in planning our monthly, daily, and hourly staffing levels and ensure we’re providing our customers with best-in-class service with up to date hiring plans. This role will play a vital part in improving forecast accuracy, reporting, and planning around floor staff utilization and efficiency. You’re excited about this opportunity because you will… Build and maintain support capacity plan models at a monthly, weekly, and interval level for a large, 24/7/365 organization. Forecast incoming contacts based on Delivery volume, Mx and Dx onboarding. Analysis on historical data to provide insights that improve support operations. Guide Short-Term staffing adjustments to address current staffing gaps. Work with our operations team to track how our staffing is being implemented and optimized. Make proactive and corrected improvements. Partner with Real Time Analysts for

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Lead DFT Engineer Job Description: Developing silicon for edge-to-cloud computing isn't just about speed; it’s about balancing high-performance data processing with extreme power efficiency and reliability in remote environments. As the Design for Test (DFT) Lead, you will be the architect of our testing strategy, ensuring our data center chips are flawlessly manufacturable and resilient enough for edge deployment. Key Responsibilities: Architectural Leadership: Define and implement the end-to-end DFT architecture for complex SoCs, including Hierarchical DFT, Scan compression, Boundary Scan and MBIST. Edge-Specific Reliability: Develop strategies for In-System Test (IST) and power-on self-test (POST) to ensure chip health in remote edge data centers. Implementation & Flow: Oversee scan insertion, ATPG (Stuck-at, Transition, Path Delay), and Memory /Logic BIST. Cross-Functional Synergy: Collaborate with Design, Physical Design, and Yield teams to ensure high test coverage while minimizing area overhead and power impact as well as timing analysis . Post-Silicon Validation: Lead the bring-up and debug phase on ATE (Automated Test Equipment) to root-cause silicon failures and optimize test time. Technical Requirements: Experience: 12+ years in DFT, with at least 2 years in a leadership or principal role. Bachelor’s degree in a related field. Tools:

Glance AI is an AI commerce platform shaping the next wave of e-commerce with inspiration-led shopping, less about searching for what you want and more about discovering who you could be. Operating in 140 countries, Glance AI transforms every screen into a stage for instant, personal, and joyful discovery, where inspiration becomes something you can explore, feel, and shop in the moment. Its proprietary models, seamlessly integrated with Google’s most advanced AI platforms, Gemini and Imagen on Vertex AI, deliver hyper-realistic, deeply personal shopping experiences across categories such as fashion, beauty, travel, accessories, home décor, pets, and more. Designed to seamlessly integrate into everyday consumer technology, Glance AI reimagines the future of e-commerce with inspiration-led discovery and shopping. With an open architecture built for effortless adoption across hardware and software ecosystems, Glance AI is creating a platform that can become a staple in everyday consumer technology. It partners with the world’s leading smartphone makers, connected TV manufacturers, telecom providers, and global brands — meeting people where they are: on mobile, smart TVs, and brand websites. Through Glance AI’s rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high-impact, performance-driven shopping journeys for brands worldwide. Part of the InMobi Group, a global technology and advertising leader reaching over 2 billion devices and serving more than 30,000 enterprise brands worldwide, Glance AI is backed by Google, Jio Platforms, and Mithril Capital. Head of Commercialization Location: Bay Area (San Mateo, CA) preferred or New York, NY What should you know about joining Glance? At Glance, we walk the talk - free yourself, dream big, and chase your passion! On joining, you'll have opportunities to make an immediate impact on

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. We're looking for an AI Product Manager who brings the full standard PM toolkit — user research, market and competitive analysis, roadmap and strategy, cross-functional delivery, and strong collaboration instincts - and applies it to products where the model underneath doesn't behave the same way twice. You have a real, hands-on feel for what different LLMs are actually good and bad at, and you use that to prototype ideas yourself, sometimes shipping small, production-quality AI features directly. You default to ownership: of the roadmap, of outcomes, of the quality bar that decides whether something's actually ready to ship, and of what an agent should be trusted to do on its own versus when a human needs to stay in the loop. That's because building AI-native products means quality is a distribution, not a pass/fail — a feature can work correctly most of the time and still need a real answer for the failure tail, since the underlying system is non-deterministic, not just complex. What you'll do Lead the roadmap and strategy for your product area, from problem discovery through delivery and post-launch iteration Lead the evaluation bar for the model-powered surfaces you're responsible for: define eval sets, identify failure modes, and know the rollback plan before a change ships Prototype product ideas directly using your own understanding of model strengths and weaknesses, and ship small, production-quality AI features yourself when that's the fastest path to

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro

About the Team The ChatGPT organization at OpenAI supports our mission by building products that bring cutting-edge AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent advances in our multimodal models have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering, unlocking entirely new creative and professional workflows. We work at the intersection of research and product, partnering closely with researchers, designers, product managers, and platform engineers to bring state-of-the-art image generation capabilities to life across ChatGPT and our mobile applications. Millions of users rely on these experiences every day to create, communicate, learn, and build. About the Role We are seeking an experienced Android Software Engineer to build and improve image generation experiences within the ChatGPT Android app. You will help define how users create, edit, and interact with visual content powered by the latest multimodal AI models. This is an opportunity to work on a highly visible product area, translating cutting-edge AI capabilities into intuitive, performant, and delightful mobile experiences used by millions around the world. ChatGPT's Android app already enables users to generate and transform images directly from their devices, and we're just getting started. In this role, you will: Build and ship new Android features that power image generation and image editing experiences. Create intuitive user experiences that make advanced AI capabilities feel seamless and accessible. Collaborate closely with Product, Design, Research, and Engineering teams to bring new multimodal capabilities to production. Drive improvements in app performance, reliability, architecture, testing, and developer tooling. Optimize media-heavy workfl

About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Software Engineer to build the research infrastructure and tooling that help OpenAI models design silicon. You’ll turn chip-design workflows into reliable environments for reinforcement learning and evaluation, and make it easier for researchers to run experiments and iterate on new ideas. You’ll move between software engineering, tool integration, and open research problems. We value strong coding fundamentals, clear technical judgment, and independent execution. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build and maintain infrastructure for reinforcement learning environments, evaluations, and long-running experiments. Integrate electronic design automation (EDA) tools into workflows for RTL generation, verification, and physical design optimization. Improve experiment reliability, reproducibility, observability, and performance; debug failures across tools, services, and infrastructure. Develop tooling and model harnesses that let researchers test ideas quickly and measure correctness and power, performance, and area (PPA). Collaborate with researchers and engineers to turn successful experiments into reusable systems and training workflows. Own ambiguous projects end to end, communicate progress, and use results to guide the next iteration. You might thrive in this role if you: Have strong software engineering fundamentals, with

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 Replit Replit is building the world's most ubiquitous AI coding agent. Replit Agent can be used by anybody to bring their ideas to life. Whether it's an app for yourself, the next great startup idea, or a tool to make you more productive at work, Replit Agent can help build it. Replit is also the leader in secure vibe coding. We protect apps, give users features to manage security risks, and help them vibe code more safely. About the role: Replit is changing how people and companies turn ideas into software. Reaching those customers requires engineering that connects acquisition to the product experience and gives teams trustworthy evidence about what works. This role goes beyond operating conventional marketing technology. You will rethink growth systems for a world where agents can observe performance, diagnose problems, take action, and learn from the result. As the founding engineer for Growth Enablement, you will set the technical direction for this area. You will build agentic systems alongside shared foundations for attribution, audiences, lifecycle engagement, referrals, and promotions. The work spans web, mobile, billing, and data. You will work directly with marketing, sales, and partnerships to find the highest-leverage problems and ship the first solutions. Successful projects will become platforms that help these teams move faster and give Replit a clearer view of what drives durable growth. You will: Design agentic growth systems that monitor performance, diagnose failures, run approved experiments, and improve from the results. Explore AI-native approaches to answer engine optimization, campaign operations, audience discovery, and measurement. Build acquisition measurement across web and mobile, in

About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with user intent. Our mission is to reduce the probability of severe unintended outcomes from increasingly capable AI agents while preserving their ability to act effectively and autonomously. Our work spans three areas: Training: Create training methods, environments and data that teach agents to make better decisions in consequential situations. We turn real-world failures into training signals that prevent similar incidents, and identify precursor behaviors and mitigations to address emerging risks. Measurements: Build evaluations and production metrics that identify emerging risks and measure whether our interventions work. Oversight: Develop oversight and system mitigation mechanisms that reduce harmful actions while preserving useful autonomy (for example future versions of auto-review ). About the Role We’re looking for strong executors with excellent judgment, comfort with ambiguity, and an understanding of frontier model research. You don’t need prior safety or alignment experience, we also welcome people that recently realized that alignment and safety is a critical area to contribute to. This role is based in San Francisco, CA. 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: Train and evaluate frontier models to reduce harmful or misaligned agent actions, forming clear hypotheses and executing independently through ambiguity. Mine incidents and build scalable measurement, data-processing, and evaluation systems that turn real failures into repeatable safety signals. Collaborate closely with post-training, capabilities, oversight, and pre-training partners to ship research-backed mitigations into large-scale training and agent systems. You might thrive in this role if you: Have demonstrated strength in research engineering, ML en