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About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet High Performance Computing (HPC) team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automati

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet Hardware team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automation to reduce manual work

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. POSITION SUMMARY CVS Health is seeking a highly skilled Staff Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Staff Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Staff Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Staff Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patterns. The id

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. POSITION SUMMARY CVS Health is seeking a highly skilled Senior Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Senior Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Senior Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Senior Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patter

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Security Engineer, dedicated to Product Security Incident Response. In this role, you will lead and architect Snowflake's product-integrated Incident Response strategy, with a primary focus on AI and LLM security. You'll design, plan, and drive the implementation of incident response capabilities across Snowflake's AI product surface - including Cortex AI, Cortex Agents, Snowflake Intelligence, and the data pipelines that power them. AS A SENIOR SECURITY ENGINEER, INCIDENT RESPONSE AT SNOWFLAKE, YOU WILL: Lead incident response for product-level security events, with deep focus on AI-specific threat vectors including prompt injection, model abuse, agent hijacking, and data exfiltration through AI workloads. Integrate IR into AI product pipelines - work directly with teams shipping Cortex features, Snowflake Intelligence, and AI-powered developer experiences to embed security requirements from design through deployment. Develop and codify our AI abuse response strategy - defining detection, containment, and remediation playbooks for LLM misuse, adversarial inputs, and AI-assisted attacks targeting Snowflake customers. Address tech debt across the AI product stack, ensuring that new Cortex and agentic architectures meet IR readiness requirements from th

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary: We are looking for a Staff Systems Engineer - Digital to join our team, the foundational layer that powers access, governance, and intelligence across our digital products. You will work horizontally across engineering, product, and AI teams, leading, owning, and evolving the shared infrastructure that every team at the company depends on. You will be the primary authority on how information is modeled, governed, and served across operational, analytical, and AI workloads - driving quality, compliance, and reliability at scale. If you thrive in a role where your architecture decisions multiply the productivity and capability of entire teams, this is the opportunity for you. Key Responsibilities: Data Architecture & Platform Ownership: Define and own the enterprise data architecture strategy across operational, analytical, and AI/ML workloads Design and govern data models, data contracts, and canonical schemas used across product and platform teams Evaluate and standardize data platform tooling — data lakes, warehouses, streaming, and serving layers (GCP BigQuery, Pub/Sub, Dataflow, or equivalent) Serve as the primary point of contact and SME for shared data platform concerns acro

ABOUT PROPRIETARY RESEARCH On our proprietary research team—Market Intelligence— you will uncover insights about markets and the broader economy through deep compliant fundamental research and applying data science and engineering techniques to alternative data sets. In partnership with our investment professionals and Compliance team, our team of analysts, data scientists and engineers work together to produce compliant research and build tools that inform our firm’s investments. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. WHAT YOU’LL DO As a Macro Analyst, Market Intelligence covering the US, you will work with alternative data to gather macroeconomic context and identify insights relevant to rates and FX markets. You will then partner with our team of data scientists and engineers to develop analyses that you deliver as synthesized insights to our investment professionals to help aid in their research processes. The work is ever evolving, affording opportunities to tackle new challenges alongside research teammates from diverse backgrounds. Specifically, you will: Analyze and interpret alternative data from multiple sources and develop subject-matter expertise on the key themes and KPIs that drive the markets within your assigned coverage Produce research for internal consumption by our investment professionals across a variety of channels, including written reports, verbal communication, data feeds, and visualizations Interact directly with our investment professionals to learn the macro investment process from them and help drive more informed investment decisions Collaborate with our proprietary research teams including Data Sourcing, Data Science, and Data Engineering, as well as Compliance, to source, evaluate, and draw value from new and existing data assets to produce actionable research for investment professionals WHAT’S REQUIRED &nb

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Lead, Senior Decision Scientist serves as a strategic analytics and ideation leader supporting Payment Integrity Affordability initiatives with a primary focus on Fraud, Waste & Error (FWE) and Special Investigations Unit (SIU) programs. This role provides leadership and guidance to a team of Decision Scientists while driving the development, evaluation, and implementation of innovative opportunities that improve affordability outcomes and strengthen Payment Integrity capabilities. The Lead Decision Scientist is responsible for establishing analytical frameworks, managing ideation pipelines, defining success metrics, and identifying cross-functional opportunities that create enterprise value across Payment Integrity programs. Required Qualifications 7+ years of experience in healthcare analytics, Payment Integrity, Fraud, Waste & Error (FWE), Special Investigations, or related healthcare operations. 5+ years of experience leading analytical projects or providing technical leadership within a healthcare environment. Demonstrated experience working with healthcare claims platforms including ACAS, QNXT, HRP, or comparable systems. Experience using SAS, SQL, Python, R, or other analytical and statistical programming languages. Experience performing advanced data analysis, opportunity identification, trend analy

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Fraud Data is the data science and machine learning team within Plaid’s Fraud organization, responsible for using data and ML to improve and scale Plaid’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across Plaid’s Fraud portfolio. As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. Define product metrics, their underlying data, and reporting and

About the Team OpenAI’s People team hires, engages, and retains world-class talent to safely build and deploy AGI that benefits all of humanity. The People Analytics team helps leaders make rigorous, evidence-based talent decisions and ensures that the systems supporting those decisions are valid, reliable, fair, and accountable. About the Role As a People Data Scientist focused on AI fairness and bias testing, you will help establish how OpenAI evaluates AI-assisted People systems and high-impact talent processes. You will design and conduct rigorous assessments to identify, measure, and mitigate potential bias across the lifecycle of models, agents, decision-support tools, and automated workflows. Your work will span the entire employee life-cycle, such as hiring, performance, promotion, employee development, workforce planning, etc. You will evaluate both technical systems and the broader human-AI decision processes in which they operate, examining not only model performance but also data quality, measurement validity, differential outcomes, human oversight, and unintended consequences. We’re looking for an experienced data scientist or applied researcher who can translate complex fairness questions into defensible evaluation strategies, scalable testing infrastructure, and clear recommendations for technical teams and senior leaders. This role is preferred to be based in San Francisco, CA. In this role, you will: Define and lead fairness and bias-testing strategies for AI-assisted People processes, models, agents, and decision-support systems from development through deployment and ongoing monitoring. Design rigorous algorithmic audits and validation studies, including adverse-impact analysis, subgroup and intersectional evaluation, error-rate analysis, calibration, measurement invariance, reliability, criterion-related validity, and sensitivity testing. Identify the appropriate fairness criteria for each use case, evaluate tradeoffs among competing definitions

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are seeking experienced professionals with a strong background in Artificial Intelligence, Machine Learning, and Cloud Architecture to join our Services Delivery team to help create exciting new offerings and capabilities for our customers! In this strategic role, you will help customers expand their use of the Snowflake Data Cloud to bring AI/ML pipelines from ideation to full production. Leveraging Snowflake’s native features and extensive partner ecosystem, you will advise clients on best practices for scaling production-ready workloads. You will design tailored AI/ML solutions, coordinate closely with customer teams and Systems Integrators, and provide the technical leadership and oversight needed to ensure successful outcomes. AS A PRINCIPAL SOLUTIONS ARCHITECT AT SNOWFLAKE, YOU WILL: Be a technical expert on all aspects of Snowflake in relation to the AI/ML workload and provide customers with best practices given Snowflakes technology stack. Work with customers to understand their AI/ML use case, discover key requirements, and architect a Snowflake-centric solution to be delivered by Services Delivery. Understand how to build, deploy and AI and ML pipelines using Snowflake features and/or Snowflake ecosystem based on customer requirements. Work hands-on where neede

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Streaming Platform team at Sentry is building the next generation of infrastructure that powers our ingestion pipelines and real-time data processing systems. Our platform ingests, processes, and distributes hundreds of thousands of events per second with low latency and high reliability. We are creating a system that makes it easy for Sentry engineers to deploy and run Streaming Applications at scale by simplifying the complexity of Kafka, scaling consumers automatically, and managing state so product teams can focus on building great experiences for developers. As part of this team, you will work on challenges at the intersection of distributed systems, real-time data processing, and developer experience. You will help us create a self-service streaming platform that improves stability, accelerates time to production, and reduces operational overhead. In this role you will Design, build, and operate components of our Streaming Platform, including Kafka, the streaming runtime, high-level APIs, and developer-facing abstractions. Implement resilient, high-throughput stream processing systems that handle unbounded datasets with strong correctness guarantees (delivery, checkpointing, watermarking, and more). Build scalable automation and control plane for Kafka fleet management and improve efficiency. Partner with product engineers to ensure our abstractions enable fast, reliable, and consistent ingestion pipelines. Improve observability, monitoring, and failover for mission-critical real-time systems. You’ll love this job if you You enjoy working on distributed systems at scale and care about reliability and

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're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. Realizing that vision requires a platform that legitimate users can trust and adversarial actors cannot exploit. We're hiring a Data Scientist to help build Replit's Trust & Safety and Anti-Abuse program from the ground up. You'll turn noisy behavioral, identity, payment, infrastructure, and content signals into the measurement systems, detections, and decisions that protect Replit's users, platform, and economics. You'll work closely with Engineering, Support, Legal, Security, Infrastructure, Money, and Growth to make abuse economically unviable while keeping friction low for legitimate users. Replit sits at the frontier of AI-native abuse. Our platform is a target for phishing and scam hosting, cryptomining, LLM token farming, card and coupon fraud, referral abuse, and increasingly, abuse driven by AI agents themselves. You'll help define how we identify, measure, and respond to these threats without compromising the experience of good users. Who You Are You're a data scientist who moves fast, goes deep, and thinks adversarially. You can spin up an analysis in hours that would take others days, not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You dig past the top-line abuse rate to understand selection effects, missing labels, policy changes, attacker adaptation, and the false positives hidden inside an aggregate metric. You understand that Trust & Safety data is imperfect and outcomes are high stakes. Ground truth is delayed, biased, and often incomple

We are seeking a visionary Answer Engine Optimization Lead to spearhead our Large Language Model (LLM) and AI platform visibility strategy (e.g., ChatGPT, Claude, Google AI Overviews, Perplexity). Reporting into the Director of Marketing Acquisition, this role will be responsible for expanding our brand authority, maximizing developer mindshare, and driving new customer acquisition by optimizing MongoDB’s presence within LLM and answer engine responses. If you thrive at the intersection of technical content architecture, structured data, community advocacy, and AI-era discovery—and you want to lead a team on the front lines of defining the next wave of search experience optimization—this is a critical leadership role designed to accelerate target audience awareness and Product-Led Growth (PLG). This role will be based remotely in the United States. Key Responsibilities Define & Execute AEO Strategy: Design and own MongoDB’s global LLM visibility growth initiatives. Develop and execute strategies focused on increasing the citation share, sentiment, and accuracy of MongoDB across various technical developer audiences and agentic AI models Team Leadership: Oversee and scale a high-performing team of SEO, AEO, and content optimization professionals, fostering a culture of rapid experimentation in the AI search space Technical Information Architecture: Collaborate with Product, Engineering, and Documentation teams to optimize MongoDB’s digital footprint for LLM crawlers. Impose best practices for structured data, schema markup, knowledge graphs, and API/documentation accessibility to facilitate flawless RAG (Retrieval-Augmented Generation) ingestion UGC Response & Community Advocacy: Coordinate a multi-team framework (including Developer Relations and Support) to ensure timely, high-quality, and LLM-friendly insights are present on critical developer watering holes (e.g., Reddit, Stack Overflow, GitHub, Wikipedia). Leverage "build in public" tactics to organicall