Large Enterprise Account Executive Auth0 Jobs

About the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-thr

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and fi nancial reporting. Team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Sta ff Software Engineer,Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs. You’re excited about this opportunity because you will... Own critical data systems that support multiple products/teams Develop, implement and enforce best practices for data infrastructure and automation Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We’re excited about you because... 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects 6+ years experience working in data platform and data engineering or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Pro fi ciency in programming languages such as Python/Kotlin/Scala 4+ years of experience in ETL orchestration and work fl ow management tools like Air fl ow Expert in database fundamentals, SQL, data reliability practices and distributed computing 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kaa/Flink/Spark Streaming Excellent communication skills and experience working

About the Team The Analytics team is looking for experienced Data Scientists and Senior Data Scientists to guide measurement, strategy, and tactical decision-making across the company across a variety of teams and levels. Data Scientists at DoorDash work to uncover insights and turn them into relevant recommendations, driving decisions for the entire organization. Analytics is integral to all operational areas at DoorDash. Please apply here for all non-managerial levels within the following analytics teams: Consumer & Growth Business Operations Dasher & Logistics Customer Experience & Integrity Merchant, Ads & Sales New Verticals International Data Science About the Role As a Data Scientist at DoorDash, you'll use your quantitative background to mentor other scientists and dive into large datasets to guide decision-making. We solve a multitude of exciting challenges including customer acquisition, fraud and support, marketing, balancing supply and demand, new city launches, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business Build full-cycle analytics experiments, reports, and dashboards using SQL, R, Python, or other scripting and statistical tools Work with and mentor junior analysts on how to use more advanced methods and solve challenges Produce recommendations and use statistical techniques and hypothesis testing to validate your findings Provide insights to help business and product leaders understand marketplace dynamics, user behaviors, and long-term trends Identify and measure levers to help move essential metrics and make recommendations Work backwards from understanding and sizing problems to ideating solutions Report aga

About the Team DoorDash Ads will become the most transparent and effective advertising channel for merchants, brands, and ad buyers/agencies of all sizes to market their offerings to engaged local audiences. We build a variety of products that are easy to use and confidently generate incremental value for advertisers, while also helping consumers discover and engage with brands they love and save money. As the analytics team our goal is to advance product development, understanding of the business, and identify opportunities for the team to drive towards our north stars. About the Role As the leader of a large, high-performing team of data scientists, you’ll own the analytics strategy for DoorDash Ads for Restaurants—one of the company’s fastest-growing and most dynamic businesses. You’ll guide a team spanning multiple levels of seniority to drive insights and decisions across a multi-sided marketplace, optimizing across consumer and merchant outcomes . In your first few months, you’ll establish clear priorities, align cross-functional partners in product, engineering, sales, and strategy, and set the analytical vision for sustainable growth. Success in this role means delivering measurable business impact, elevating the quality of analytics across the organization, and building systems that balance advertiser ROI, consumer experience, and platform health. You will report into the Senior Director of Analytics on our Ads team in our Ads & Promos organization. You’re excited about this opportunity because you will… Lead and develop a high-performing analytics team, providing mentorship, feedback, and clear career development pathways. Define and drive the analytical and product roadmap by setting measurable goals and aligning cross-functional teams around success metrics. Partner closely with product, engineering, and go-to-market teams to uncover insights, optimize funnels, and inform high-impact decisions. Apply advanced analytical methods—such as co

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Senior Data Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. This is a hybrid position and you must be located in Sunnyvale, San Francisco, or Seattle. You're excited about this opportunity because you will... Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because... 5+ years of professional experience 3+ years experience working in data engineering, business intelligence, or a similar role Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms Excellent communication skills and experience working with technical and non-tec

CAPCO POLAND *We are looking for Poland based candidate. Capco is a fully independent, global management and technology consultancy. For 25 years we have combined innovative thinking with deep industry knowledge to deliver business consulting, digital transformation and technology services to Finance and Energy markets. Our collaborative and efficient approach helps clients reduce costs and manage risk and regulatory change while increasing revenues. We are thinkers, innovators, and disruptors. We are small enough to care but large enough to matter. We are seeking a highly skilled Security Operations Engineer to support the expansion of a strategic security program focused on onboarding critical applications into enhanced monitoring capabilities.In this role, you will play a key part in building and optimizing SIEM detection capabilities, supporting threat verification, and enabling regulatory alignment with DORA (Digital Operational Resilience Act) requirements by the end of 2026. You will work at the intersection of SIEM engineering, threat modelling, and security operations , contributing directly to improving detection accuracy and strengthening overall security posture. Key Responsibilities: Detection Engineering: Design, build, and optimize SIEM detection rules (with a focus on Microsoft Sentinel) Testing & Automation: Develop and execute test cases for detection logic; automate validation processes using scripting Application Onboarding: Support onboarding of critical applications into the security monitoring ecosystem Requirements Gathering: Collaborate with application teams to define logging requirements and detection use cases Workshop Facilitation: Lead and moderate workshops with stakeholders to align on threat scenarios and security capabilities Technical Documentation: Produce clear and comprehensive documentation covering detection logic, threat models, and validation results Collaboration: Work closely with SOC, enginee

Research Engineer, Applied AI Location: Bangalore (or throughout India remote-friendly with travel) About EnCharge AI: EnCharge AI is building the next generation AI platform. Our novel in-memory-computing architecture delivers a 10x step-function improvement in compute energy efficiency and performance for AI inference workloads. As the demands of artificial intelligence move beyond today's models, we believe fundamental underlying infrastructure must evolve. We are an experienced team of AI researchers, silicon & systems engineers, and architects backed by leading investors, poised to become the essential platform for the next wave of AI innovation. The Opportunity: Modern AI workloads—from large language models to diffusion-based generators to multimodal systems—represent some of the most compute-intensive frontiers in AI, and some of the most promising applications for our hardware’s energy efficiency advantages. We’re building a vertically integrated AI stack that will showcase the transformative potential of our silicon while delivering real value to customers today. We are seeking a Research Engineer to push the boundaries of AI model capability, quality, and efficiency. You’ll build fine-tuning and post training pipelines, develop rigorous benchmarking frameworks, and work at the intersection of ML research and hardware-aware optimization—ensuring our models run beautifully on our silicon. This is a role for someone who thrives at the boundary between research and engineering. You’ll read papers, implement techniques, and ship production-quality code—all in service of making AI inference faster, cheaper, and better. Key Responsibilities: Algorithmic Acceleration: Research and implement state-of-the-art techniques to accelerate AI inference—quantization, sparsity,

Joining Capco means joining an organisation that is committed to an inclusive working environment where you’re encouraged to #BeYourselfAtWork. We celebrate individuality and recognize that diversity and inclusion, in all forms, is critical to success. It’s important to us that we recruit and develop as diverse a range of talent as we can and we believe that everyone brings something different to the table – so we’d love to know what makes you different. Such differences may mean we need to make changes to our process to allow you the best possible platform to succeed, and we are happy to cater to any reasonable adjustments you may require. You will find the section to let us know of these at the bottom of your application form or you can mention it directly to your recruiter at any stage and they will be happy to help. About Capco Capco is a global technology and business consultancy, focused on the financial services sector. We are growing at fast pace in our Italian office, the opportunity for growth is large, accessible, and immediate. We are passionate about helping our clients succeed in an ever-changing industry. Capco is going through a significant growth journey, now is a very good time to join us as we expand our consulting team in Italy. Role Description: We are looking for a Lead AI Engineer to join our Capco AI Lab and help design and build production-grade AI solutions for our clients. This is a senior , hands-on engineering role for someone with a strong software engineering background who has developed deep expertise in Generative and Agentic AI. You will make technical and architectural decisions, guide other engineers and, importantly, continue to write and review production code yourself . You will work on complex AI systems covering LLM orchestration, AI agents, RAG, tool and function calling, evaluation and observability, taking solutions from early prototypes through to scalable production environments. The role also involves working directly w

Role Description *** Technical Skills:** Exposure to Liquidity Risk reports – PRA LCR, PRA NSFR PRA110 and ILM Able to understand regulations on liquidity risk and write requirements required for remediating adjustments An understanding of the principles of Finance data and report Proficient in interrogating databases via SQL queries An understanding of systems delivery lifecycles and testing principles Proficient in the use of test tools (such as Quality Centre) and test processes (e.g. defect management) Be able to formulate test strategies and confident in running a successful test phase An appreciation of systems and data architectures Proficient in Microsoft Office applications (Word, Excel, Visio, PowerPoint, Project) ** Personal & Professional Skills:** Educated to minimum of post graduate degree level or equivalent Personal Skill Requirements** Ability to professionally and effectively present information Proficiency in problem solving A self-starter with excellent written/verbal communication skills Desire and commitment to make a difference Experience Financial Services Test Experience across both internal reporting and regulatory requirements Experience in testing, driven by IT systems implementation or enhancement, across a large organisation Experience of working in a large banking organisation preferred The role holder will be responsible to functionally understand and test our liquidity core release requirements He/ She is required to perform a detailed data validation to ensure the data reflects accurately across all liquidity returns for all applicable regulations - PRA/EBA/HKMA/US FED etc. He/She needs to furnish UAT dashboards and walkthrough the Reporting Ops of the changes introduced by liquidity core release requirements He/She is responsible to handle various queries raised by Reporting Ops and drive the UAT sign off discussions for asuccessful liquidity release implementation *** Experience:** Financial Services Testing: Experience in tes

Job Title: Liquidity - BA Reporting Applying predefined regulatory rules and mappings to support regulatory submissions under guidance/supervision. Basic variance analysis and reconciliation activities Understanding and applying documented procedures for regulatory reporting. Regulatory impact assessments and benchmarking activities using predefined methodologies, with interpretation performed under supervision. Strong understanding of regulatory reporting frameworks (PRA, EBA, ECB, Basel, Liquidity, Capital, IRRBB) Solid grounding in finance, accounting, balance sheet & RWAs. Proven experience working in large, global financial institutions Documenting business and functional requirements.. Experience in project governance, RAID/status reporting, steerco delivery, and coordinating across BA/IT/testing workstreams. Exposure to controls frameworks, audit readiness, and issue remediation within regulatory reporting environments. Familiarity with collateral management, intraday liquidity, or supply chain management reporting domains. Experience with reporting remediation, communications delivery, or governance within regulatory change programmes Desirable: Provides subject matter expertise and judgement to assess and resolve complex, ambiguous, or emerging regulatory reporting requirements (e.g. PRA, ECB), where established procedures or precedents may not exist

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Role Type: Contract / Internship (High-Commitment) Location: Bengaluru (On-site) Travel: Extensive travel across India Duration: 6 Months Working Hours: 6 days/week | Project-dependent hours Role Overview We are looking for a Trainer (Intern) to support the onboarding, training, assessment, and certification of Field Operators working on large-scale field operations. This is a hands-on training role, not a conventional classroom-only position. You will be responsible for taking candidates through the complete training journey, from onboarding and practical training to assessment and certification. The role requires extensive travel across India, strong communication skills, confidence in managing groups, and the ability to strictly enforce SOPs and make objective certification decisions. Key Responsibilities 1. Training & Onboarding Conduct classroom and hands-on training sessions for Field Operators.| Explain SOPs, technical processes, and field procedures in a simple and actionable manner. Demonstrate correct equipment handling and operating procedures. Manage training batches and maintain discipline, engagement, and focus. Take ownership of trainees from onboarding through certification. 2. Assessment & Certification Conduct knowledge quizzes and practical assessments. Evaluate candidates against defined assessment criteria. Make objective Select / Reject decisions based on performance. Provide corrective coaching and feedback where required. Ensure only candidates meeting

About the Role OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models. We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience. You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments. Key Responsibilities Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency. Develop forecasting models for inference demand across products, regions, and model families. Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities. Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies. Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs. Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions. Collaborate with Product, Research, Finance, and Infrastructure teams to align compute planning with business growth and model roadmaps. Communicate technical findings clearly to both engineering teams and executive leadership. Qualifications MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience). 5+ years of experience working in the infrastructure data science space. Strong ex

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 This is an opportunity to serve as a key partner and advisor on Notion’s Business Operations team, working primarily with our Engineering, Product, & Design teams. Business Operations is a cross-functional team that partners with senior leaders across the company, focusing on high-impact strategic projects and analysis. In this role, you’ll work hand-in-hand with leadership to identify, structure, and act on the most challenging strategic and operational questions impacting our business. This role is based in San Francisco, CA. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve Build trusted relationships with cross-functional leaders to define and implement strategy across all Notion products, driving increased value to our users and our business Structure complex, ambiguous strategic problems for the Notion leadership team, defining clear hypotheses and building detailed business cases and quantitative models that will

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: This role will be based in San Francisco. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. You’ll build the systems that let any knowledge worker leverage fast, scalable databases without having to become a DBA. You’ll be a hands-on technical leader, helping set the architectural direction and roadmap as we take a new product from early alpha to general availability. You’ll work directly with early customers to shape foundational technical and product decisions. Then, together, we’ll work on scaling as adoption and workloads grow. This is a backend-leaning role with work spanning the stack. You might build the systems that provision and manage a fleet of customer Postgres instances, design how user-defined schemas evolve safely, or make complex queries execute efficiently. You’ll also follow those systems into the product: improving how a table loads, how users understand a slow operation, or how an agent safely works with their data. You’ll

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