Engineering Manager, Financial Data Quality

About Our TeamThe Financial Engineering team within Applied Engineering is dedicated to ensuring that our products are monetized efficiently, catering to the diverse needs and scales of our clients. We work hand-in-hand with the Go-To-Market (GTM) and Finance teams to continuously refine our billing systems and meet evolving internal requirements.Position Ov…

About Our TeamAt OpenAI, our Financial Engineering (FinEng) team plays a pivotal role in shaping the financial landscape of our products, including pricing strategies, packaging, checkout processes, payment systems, and subscription models. We collaborate closely with Product, Engineering, Risk, Finance, and Go-to-Market teams to ensure that the payment experience for OpenAI products is seamless, reliable, and efficient on a global scale.About This PositionAs a Data Scientist within the FinEng team, you will take ownership of analytics and experimentation initiatives aimed at enhancing our checkout and payment systems, subscriptions, and pricing & monetization strategies. Your responsibilities will include defining key performance metrics, building robust data assets, and designing experiments that drive conversion rates, minimize churn and payment failures, and broaden our global payment options. Your contributions will have a direct impact on revenue, customer satisfaction, and our international scaling efforts.This position is located in San Francisco, CA, and operates under a hybrid work model requiring three days in the office each week. We also provide relocation assistance for new hires.Your ResponsibilitiesLead analytics and experimentation for checkout and payment systems across different methods and regions, focusing on improving conversion while managing risk and latency.Develop and implement an experimentation framework for our in-house checkout process, defining success metrics, executing staged rollouts, and applying offline incrementality for scenarios where online testing is not practical.Create operational transparency and establish source-of-truth data in partnership with the FinEng Data Engineering team—develop team-level metrics, SLAs, and self-service dashboards that promote proactive decision-making.Drive analytics for subscription, retention, and monetization strategies—ensure readiness for new subscription feature launches, reduce involuntary churn through targeted retrials and nudges, and create frameworks to optimize pricing strategies based on elasticity and foreign exchange considerations.Ideal Candidate ProfileMinimum of 5 years of experience in a quantitative role (data science, product analytics, or experimentation) within dynamic or fintech environments.Proficient in SQL and Python, with demonstrated experience in designing and interpreting A/B tests and quasi-experimental designs.Skilled in developing product metrics from the ground up and operationalizing them for effective decision-making.Strong communication skills, capable of effectively engaging with Product Managers, Engineers, Risk and Finance partners, and executive leadership.

Slash Financial creates tailored financial infrastructure for businesses in a variety of sectors. The company blends the reliability of traditional banking with high yields, strong rewards, and security, while offering features that help clients operate more efficiently and profitably. Founded in 2021, Slash Financial processes over $10 billion in business transactions each year. The company recently secured $100 million in Series C funding led by Ribbit Capital, with additional backing from Khosla Ventures, Goodwater Capital, NEA, and Y Combinator. This investment supports ongoing product development and expansion into new markets. Headquartered in San Francisco, the team emphasizes in-person collaboration at the office. Role overview The GTM Engineer will join a group dedicated to building a financial platform for complex, global businesses. This position involves close work with customers and the sales team, contributing at every stage from initial discovery to implementation and ongoing support. Direct client interaction is a key part of this job. Insights gathered from these engagements shape solutions and help transform custom work into platform features that serve thousands of businesses. This is a hands-on, customer-facing position. GTM Engineers write code, tackle technical challenges, and take responsibility for outcomes. Location This position is based onsite at the San Francisco office.

CoreWeave, listed on Nasdaq as CRWV since March 2025, provides cloud solutions trusted by AI labs, startups, and global enterprises. The company continues to expand its infrastructure, focusing on reliability and quality in every aspect of its operations. Learn more at www.coreweave.com. Role overview This Quality Engineer (QMS) role centers on building, scaling, and maintaining a Quality Management System for data center operations. The position emphasizes standardizing processes, ensuring compliance with ISO standards, and driving ongoing improvement. The work supports a preventive quality framework as CoreWeave grows across multiple locations. What you will do Design, implement, and refine an ISO-compliant Quality Management System for data center operations Create standardized processes, SOPs, and governance frameworks Promote preventive, systems-based quality practices Utilize digital QMS tools such as ETQ or Arena to automate and manage workflows Oversee audits, corrective and preventive actions (CAPA), document control, and training priorities Establish and manage document control systems Develop and deliver training programs to maintain audit-ready, ISO-compliant documentation Lead internal audit programs and assist with external audits and certification readiness Identify process deficiencies and drive corrective actions Participate in root cause analysis and standardize CAPA processes Implement systemic improvements across multiple sites Develop KPIs, dashboards, and reporting tools to track quality performance Collaborate closely with Data Center Operations, Engineering, Supply Chain, and other teams Requirements Proven experience in data center operations, quality management systems, and industry standards Understanding of ISO standards and preventive quality practices Familiarity with digital QMS platforms such as ETQ or Arena Strong ability to work across teams and functions This position is available in Livingston, NJ, New York, NY, Sunnyvale, CA, San Francisco, CA, and Bellevue, WA.

Slash Financial develops business banking infrastructure tailored for modern companies. The team blends the dependability of traditional banking with features that help businesses operate more efficiently and stay ahead in their markets. Since its start in 2021, Slash Financial has grown quickly, now processing over $10 billion in annual transactions across various industries. Backed by a recent $100M Series C led by Ribbit Capital and supported by Khosla Ventures, Goodwater Capital, NEA, and Y Combinator, the company is focused on expanding its product offerings and scaling operations. The company values in-person teamwork and maintains a hands-on culture at its San Francisco office. Role overview As an Applied AI Engineer at Slash Financial, you will join Slash AI Labs, a team dedicated to integrating AI throughout the company’s financial platform. This early-stage role shapes the direction of Slash’s AI capabilities, focusing on building production-ready AI systems within a rapidly evolving fintech environment. What you will do Develop and release full-stack AI features, including prompt engineering, agent orchestration, React interfaces, and API integrations. Enhance the agent runtime by improving orchestration, tool execution, MCP servers, graph-driven conversation states, and context compaction. Design agent experiences for web, Slack, and API-based user interactions. Create internal AI tools such as model evaluation frameworks, prompt management systems, and utilities for LLM observability. Work directly with Anthropic and OpenAI APIs, the Vercel AI SDK, and Slash’s custom orchestration layer to address tool-calling and multi-step reasoning challenges. Scale and optimize AI infrastructure, including inference routing, model tiering, prompt caching, and streaming on AWS/EKS. Requirements Experience deploying full-stack AI products in production. Strong understanding of AI technologies and frameworks. Background in orchestration and management of AI models. Ability to design applications that function across multiple platforms and interfaces. Strong problem-solving skills and comfort working in a changing environment. Location This position is based onsite at the San Francisco office.

Slash Financial develops business banking infrastructure tailored for real operational demands. Since its founding in 2021, the company has processed over $10 billion in annual business transactions across several industries. With $100M in Series C funding from investors including Ribbit Capital, Khosla Ventures, Goodwater Capital, NEA, and Y Combinator, Slash continues to grow its product offerings and market presence. The San Francisco headquarters fosters a collaborative, in-person work environment. Role overview The Senior Infrastructure/Platform Engineer will take a hands-on role in scaling and strengthening the core platform behind Slash’s banking products. This position involves designing, building, and maintaining infrastructure to support rapid company growth and high transaction volumes. The work spans AWS cloud operations, Terraform, Kubernetes, and related systems. This engineer will help shape infrastructure strategy and make key decisions on performance, observability, security, and deployment. What you will do Lead the development of next-generation database, real-time workflow, and container orchestration infrastructure. Scale and enhance the Kubernetes (EKS) platform, CockroachDB clusters, Kafka (MSK), Temporal workflows, and ElastiCache Redis. Collaborate with engineering teams to establish and scale best practices using AWS ALB, WAF, Route 53, OpenSearch, S3, and Vercel. Create and maintain abstractions in Terraform and Pulumi to streamline architecture and assist product teams. Improve the speed and reliability of CI/CD pipelines. Tackle complex scaling, performance, and low-latency challenges within a monolithic architecture. Location This role is based in the San Francisco office and supports an in-person work culture.

About Us:At Notion, we empower individuals and teams to create stunning productivity tools tailored to their unique workflows. In a digital landscape crowded with applications and tabs, our platform unifies documents, notes, projects, calendars, and emails—all enhanced with AI capabilities to streamline tasks and provide quick insights. Trusted by millions, including industry leaders like Toyota, Figma, and OpenAI, Notion is chosen for its versatility, helping users optimize their time and resources.We believe in the value of in-person collaboration, making it a cornerstone of our company culture. To foster teamwork, all employees are required to work from our San Francisco office on Mondays, Tuesdays, and Thursdays—our designated Anchor Days. Certain roles may necessitate additional in-office presence.About The Role:As our company expands at an impressive pace, we are on the lookout for skilled Data Engineers to join our finance team. In this role, you will be instrumental in constructing robust datasets and data pipelines that underpin our financial reporting. Your work will bridge our product, financial, and operational systems, creating reliable processes that drive our growth. If you have a passion for data analytics, complex modeling, and innovative problem-solving, we would love to have you on board.What You'll Achieve:Develop essential datasets that act as the definitive sources for Notion’s financial reporting, integrating information from financial systems, business databases, and our product.Collaborate closely with our Finance, Monetization Engineering, Business Intelligence, and Data Science teams to address critical financial analysis and reporting requirements.Design, construct, and oversee data pipelines that not only meet current demands but are also scalable as our data needs grow.Facilitate widespread access to high-quality financial data across the Finance, Staff, and go-to-market teams.Skills You'll Need to Bring:A minimum of 4 years of experience as a data engineer, focusing on building core datasets and supporting various business sectors, particularly in product and high-volume data environments. A strong enthusiasm for analytics use cases, data modeling, and tackling intricate data challenges is essential.Experience in creating integrations and reporting datasets for payment, financial, and business systems such as Stripe, NetSuite, Adaptive, Anaplan, Salesforce, or equivalent.A proactive mindset, with the ability to gather and synthesize high-impact needs from business partners, designing and implementing suitable technical solutions.

About HeartFlow HeartFlow, Inc. develops medical technology to improve the diagnosis and management of coronary artery disease. The company’s flagship HeartFlow FFRCT Analysis uses advanced AI to create non-invasive, color-coded 3D models of coronary arteries, helping clinicians understand how blockages impact blood flow. HeartFlow’s integrated heart care platform supports clinicians in identifying stenoses (RoadMap™ Analysis), assessing coronary blood flow (FFRCT Analysis), and characterizing atherosclerosis (Plaque Analysis). HeartFlow is publicly traded (HTFL) and recognized internationally for healthcare innovation. Its solutions are approved in the US, UK, Europe, Japan, and Canada, and have supported care for over 500,000 patients worldwide. Role Overview: Senior Manager of Device Quality Engineering The Senior Manager of Device Quality Engineering leads the global strategy for software quality and design excellence at HeartFlow. This role builds and manages a high-performing team, connecting fast-moving Agile development with the rigorous demands of medical device regulations. The team’s work covers digital health solutions, including Software as a Medical Device (SaMD) and AI/ML technologies, with a focus on safety, security, compliance, and scalability. Main Responsibilities Direct the end-to-end design control process within the Software Development Lifecycle (SDLC). Develop and implement a roadmap for compliance, security-by-design, and readiness for global regulatory requirements. Mentor and develop future leaders in quality engineering. Bridge Agile software development practices with medical device regulatory standards. Location San Francisco Bay Area, California, United States

Our VisionAt Reflection AI, we are dedicated to developing open superintelligence and ensuring it is accessible to everyone.We are pioneering open weight models for individuals, agents, organizations, and even nations. Our diverse team of AI researchers and industry pioneers hail from esteemed organizations such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, Anthropic, and many others.Position OverviewIn the rapidly evolving field of AI, data has become indispensable for innovation. Notable progress in recent years has stemmed more from enhanced data quality than from novel architectures.As a valued member of our Data Team, you will be responsible for ensuring that the datasets used to train and assess our models are of exceptional quality, reliability, and effectiveness. Your contributions will directly influence our models' capabilities in areas such as agentic tool usage, long-term reasoning, and ensuring robust safety alignment.Collaborating with elite researchers within our post-training teams, you will help transform abstract concepts of “good data” into tangible, scalable standards for extensive data initiatives. We seek engineers who possess a strong foundation in engineering principles paired with a genuine curiosity about data quality and its effects on model performance.Working closely with our post-training teams, your responsibilities will include:Managing upstream data quality for LLM post-training and evaluations by analyzing expert-generated datasets and implementing quality benchmarks for reasoning, alignment, and agentic applications.Collaborating with research and post-training teams to translate requirements into quantifiable quality indicators and offering actionable insights to external data providers.Developing, validating, and expanding automated quality assurance methods, including LLM-as-a-Judge frameworks, to consistently assess data quality across large-scale projects.Creating reusable quality assurance pipelines that consistently supply high-quality data to post-training teams for model training and evaluation.Tracking and reporting on data quality trends over time, fostering continuous improvements in quality standards, processes, and acceptance criteria.QualificationsSolid engineering principles with experience in building data pipelines, quality assurance systems, or evaluation workflows tailored for post-training data and agentic environments.Meticulous and analytical, capable of pinpointing failure modes, inconsistencies, and nuanced issues that influence data quality.A robust understanding of the impact of data quality on model behavior and performance.

Our MissionAt Reflection AI, we are dedicated to creating open superintelligence and making it universally accessible.We are pioneering open weight models designed for individuals, agents, enterprises, and even nations. Our talented team consists of AI researchers and innovators from leading organizations such as DeepMind, OpenAI, Google Brain, Meta, Character.AI, and Anthropic.Role OverviewData is becoming increasingly vital in the realm of AI advancements. Recent significant breakthroughs have frequently stemmed from enhanced data rather than new architectures.As a vital member of the Data Team, your primary role will be to guarantee that the data utilized for training our models adheres to the highest standards of quality, reliability, and impact. You will have a direct influence on our models' performance in essential capabilities.Collaborating with exceptional researchers on our pre-training teams, you will help transform abstract concepts of "good data" into specific, quantifiable standards applicable across extensive data campaigns. We are seeking engineers who possess robust engineering skills combined with a profound curiosity about data quality and its relevance to model performance.In close partnership with our pre-training teams, you will:Take ownership of upstream data quality for LLM pre-training, functioning as either a specialist or generalist across various languages and modalities.Collaborate with research and pre-training teams to convert requirements into measurable quality signals, providing actionable feedback to external data vendors.Incorporate human-in-the-loop processes while designing, validating, and scaling automated QA methods to consistently measure data quality across large-scale campaigns.Create reusable QA pipelines that ensure the delivery of high-quality data to pre-training teams for model training.Continuously monitor and report on data quality, driving ongoing improvements in quality standards, processes, and acceptance criteria.Candidate ProfileStrong engineering background with experience in building data pipelines, QA systems, or evaluation workflows for pre-training data.Detail-oriented with an analytical mindset, capable of identifying failure modes, inconsistencies, and nuanced issues affecting data quality.Solid understanding of the influence of data quality on pre-training, with the capacity to translate quality concerns into tangible signals, decisions, and feedback.

Join collate as a Data Quality and Labeling Specialist in San Francisco, where you'll play a crucial role in ensuring the accuracy and relevance of data used across our platforms. Your expertise will help maintain high standards of data quality, enabling our teams to make informed decisions based on reliable insights.

Role overview Chime seeks a Data Governance Engineer based in San Francisco, CA. The role centers on protecting the quality and integrity of data assets throughout the organization. This engineer will partner with teams across departments to help shape and apply data governance frameworks that support Chime’s business needs. What you will do Develop and implement data governance processes and frameworks Work with teams from various parts of the company to ensure data management aligns with business objectives Support compliance with regulatory requirements related to data Promote data quality and consistency across systems Requirements Technical skills in data management and governance Experience with data governance frameworks Strong interest in data quality and compliance Ability to collaborate effectively with colleagues from multiple disciplines Why join This role offers a chance to work with new technologies and help shape the direction of Chime’s data strategy. The team values technical skill and a real commitment to responsible data management.

Company OverviewDeepgram stands at the forefront of the rapidly evolving trillion-dollar Voice AI sector, offering cutting-edge real-time APIs for speech-to-text (STT) and text-to-speech (TTS). Our platform empowers over 200,000 developers and more than 1,300 organizations—including industry leaders like Twilio, Cloudflare, and Jack in the Box—to create scalable voice solutions that are 'Powered by Deepgram'. Our unparalleled accuracy, low latency, and cost efficiency are achieved through advanced voice-native foundation models that are accessible via cloud APIs or as self-hosted and on-premises software. With backing from a recent Series C funding round led by top global investors, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words, making us the foremost authority in voice technology.Company Operating RhythmAt Deepgram, we cultivate an AI-first culture—embracing AI as an essential component of our operations, innovation, and performance metrics. Every team member is encouraged to actively experiment with advanced AI tools and integrate them into their workflows. Success in our organization is measured by the effective application of AI, and a creative, consistent approach to leveraging the latest capabilities is paramount. Candidates should be enthusiastic about adopting new models and adapting quickly to changing environments, as our pace is dictated by the evolution of AI technology.The OpportunityAs the QA Engineering Manager, you will play a critical role in maintaining the integrity of Deepgram's rapid release cycles, ensuring that quality, compliance, and customer trust are never compromised. You will serve as the quality owner across various product lines, instilling a testing-oriented mindset within our engineering culture and scaling it alongside our growth.What You'll DoOwn QA Strategy & Execution: Design and implement a comprehensive test strategy across products, incorporating both manual and automated testing with regular validation cycles.Build & Lead Team: Oversee, mentor, and expand a skilled QA team of engineers and specialists.Cross-Engineering Alignment: Collaborate with product and engineering managers to integrate testing practices into every facet of development.

Join Exa as we embark on an ambitious journey to create a cutting-edge search engine tailored for AI applications. Our team is dedicated to constructing a robust infrastructure capable of crawling the web, training advanced embedding models for indexing, and building highly efficient vector databases in Rust for optimal search performance. With our state-of-the-art $5M H200 GPU cluster, we consistently engage tens of thousands of machines to deliver unparalleled results.As the Engineering Manager, you will lead a dynamic team, fostering innovation and driving us towards achieving groundbreaking technological advancements. Our team is not only exceptionally skilled but also a joy to work with, making this an exciting opportunity.

We are seeking a visionary Director of Financial Data & Analytics to lead our data-driven initiatives at Spoton. In this role, you will be responsible for harnessing data insights to inform strategic decisions, drive operational efficiencies, and support our financial growth.Your expertise will guide the development of robust analytical frameworks and models that enhance our financial forecasting and reporting processes.

Accordion is seeking a Manager of Quality Engineering & AI Validation to guide a team focused on upholding quality standards in AI projects. This position is based in several major cities, including Atlanta, Boston, Charlotte, Chicago, Dallas, Los Angeles, New York, and San Francisco. Role overview This leadership role centers on shaping and maintaining AI validation processes. The manager will play a key part in developing and refining methodologies that support reliable, high-quality AI solutions for clients. What you will do Lead a quality engineering team dedicated to AI-driven initiatives Oversee and improve quality assurance protocols Implement thorough testing strategies to ensure product reliability Collaborate with cross-functional teams to boost product performance Requirements Strong background in quality engineering Experience with AI technologies Demonstrated leadership skills Interest in developing and managing validation processes

Join our innovative team at collate as a Quality Engineer specializing in therapeutics. In this role, you will ensure the highest standards of quality are maintained in our therapeutic products, contributing to groundbreaking advancements in healthcare. Your expertise will be pivotal in developing and implementing quality assurance processes that meet regulatory requirements and enhance product reliability.

About FaireFaire is a dynamic online wholesale marketplace dedicated to empowering local businesses. We believe in a future where independent retailers can thrive and compete against retail giants like Walmart and Amazon. By harnessing technology, data, and machine learning, we connect a vibrant community of entrepreneurs globally. Imagine helping your favorite local boutique source outstanding products from around the world to enhance their offerings. Our mission is to provide the tools and insights that enable small businesses to succeed in a competitive landscape.By championing the growth of independent businesses, Faire fosters positive economic impacts within communities worldwide. We are on the lookout for intelligent, resourceful, and passionate individuals to join our team as we drive the shop local movement. If you share our commitment to community, we invite you to be part of ours.About this roleAt Faire, we leverage advanced machine learning and data insights to transform the wholesale industry, enabling local retailers to stand strong against larger competitors. The Data Science team is pivotal in developing and sustaining a variety of algorithms and models that enhance our marketplace. We focus on creating innovative machine learning models that empower our customers to succeed.As a member of the Brand Data Science team focused on Listing Quality, your role will involve enhancing the quality of product listings, enabling retailers to effectively discover and assess products on Faire. You will apply ML and AI to address key challenges, including improving image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. Utilizing deep learning, multi-modal LLMs, and a human-in-the-loop approach, you'll deliver high-performance solutions. In this rapidly evolving domain, you will be at the forefront of applying cutting-edge technology to drive tangible outcomes. You will independently design and implement solutions while collaborating with the cross-functional Listing Quality pod, which includes product, design, engineering, analytics, and operations, to tackle challenges comprehensively.

At Oura, we are dedicated to empowering individuals to unlock their inner potential. Our award-winning products, including the Oura Ring and its connected app, provide our global community with insightful data about their readiness, activity levels, and sleep quality. By offering daily insights and actionable steps, we have helped millions enhance their overall health and embrace healthier lifestyles.Our commitment to empowerment extends to our team as well. As a rapidly growing company focused on enhancing the health and happiness of individuals, we prioritize providing our employees with the resources they need to succeed, both personally and professionally.We are currently seeking a Senior Manager of Sustaining Quality Engineering to join our dynamic Supply Chain team in San Francisco, California. In this pivotal role, you will bridge the gap between Oura’s Manufacturing, R&D, and Member Experience teams. This is a unique opportunity to lead a talented group of engineers while directly contributing to crucial technical deliverables, ensuring the quality of Oura products from development through to sustaining operations.A primary responsibility in this role will be to continuously enhance product quality from launch to sustaining operations. You will leverage field data to inform decisions that minimize field failures, reduce warranty claims, and drive ongoing improvements across the supply chain. You will play a vital role in establishing and optimizing the Engineering Field Failure Analysis (EFFA) process flow, leading comprehensive Failure Analyses (FA) with both Oura and supplier teams. Your contributions will be essential in developing and implementing effective Corrective Actions (CA) through Design of Experiments (DOEs) and Product Release Qualifications (PRQs). You will collaborate closely with Hardware, Software, and Customer Support teams to enhance troubleshooting workflows and proactively monitor known and emerging issues within the EFFA program.Beyond your hands-on responsibilities, you will spearhead sustaining quality initiatives across various offices, programs, and manufacturing sites. You will be responsible for establishing robust quality systems at suppliers to ensure reliable data collection and analysis for critical decision-making. Your long-term strategies will focus on continuously improving the Oura Supply Chain and enhancing the overall customer experience. This includes planning, developing, and implementing measurement methods, control plans, and other supply quality engineering processes to guarantee part and product quality—from initial concept through to high-volume production in our complex global environment.

Join Gusto as an Associate Principal in Financial Data, where you will play a pivotal role in shaping our financial data strategy. You will leverage your analytical skills to drive insights, enhance decision-making processes, and contribute to the growth of our financial data capabilities. Collaborate with cross-functional teams to ensure our data infrastructure supports our mission of providing exceptional services to our clients.