Lead Manager 2c Software Engineering Data Platform Manager Manager Jobs

We are seeking an experienced and detail-oriented US Payroll Specialist to oversee our end-to-end multi-state payroll operations. In this role, you will ensure accurate, timely, and compliant payroll processing for all US-based employees while managing internal payroll initiatives. The ideal candidate is a strategic problem-solver with deep expertise in US labor laws, taxation, and ADP+Workday payroll systems. You will: Full-Cycle Payroll Processing: Oversee the accurate and timely processing of multi-state bi-weekly and semi-monthly payrolls for over a thousand exempt and non-exempt employees across most of the USA. Compliance & Taxation: Ensure strict adherence to federal, state, and local tax laws, as well as FLSA regulations. Monitor regulatory changes and update internal systems accordingly. Year-End Processing: Manage year-end payroll activities, including W-2 and W-2c generation, fringe benefit reporting, and annual tax reconciliations. Cross-Functional Collaboration: Partner closely with HR to ensure accurate data flow for onboarding, offboarding, benefits deductions, and compensation changes. Ability to work with Accounting to ensure accurate general ledger mapping, month-end close procedures, and payroll account reconciliations. System Administration & Optimization: Act as the primary subject matter expert for our payroll system (e.g., Workday, ADP). Identify bottlenecks, recommend process improvements, and lead system upgrades or implementations. Issue Resolution, Continuous Improvement & Auditing: Conduct regular audits of payroll data to identify and resolve discrepancies. Serve as the ultimate point of continuous improvement with AI and other methodologies to ensure Scale’s payroll processes are best in class. Ideally you'd have: 5+ years of payroll experience. Strong organizational skills; the ability to get all priority tasks completed by the end of each day. Confidentiality and integrity. Accuracy under pressure and extreme attention to

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join The Integrations & Application Engineering team owns the integration and automation platforms at Airbnb. We enable teams across the company to self-serve in connecting their systems and automating solutions, and we integrate Airbnb’s enterprise systems end-to-end. The team also builds and manages custom in-house solutions and the application infrastructure that supports them. This is a hybrid IC and people-leadership role focused on Finance integrations and automations. As a Tech Lead Manager, you will lead and grow a team of engineers while operating hands-on at a senior IC level, setting technical direction, owning delivery, and writing and reviewing code yourself. We’re looking for someone with deep ERP product knowledge who builds integrations in general-purpose languages, takes ownership of systems and people, and is enthusiastic about applying AI, building tools and integrations with Claude Code that extend what the team can do. A Typical Day Lead the Finance and ERP integration practice: set direction, run initiatives in parallel, and own the systems and processes your team supports. Balance management with hands-on work: unblock the team, review designs and code, and build complex integrations, backend services, APIs and MCPs yourself. Partner with Finance, Procurement, and cross-functional teams to translate requirements into integrations, automations, and reporting. Coach and grow engineers and contractors through design reviews, architecture discussions, and career development. Own the smooth operation of month-end financial integrations and reporting, proactively surf

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role We are looking for an Autonomy Leader to drive the technical roadmap for the systems that validate and verify the intelligence of the NuroDriver. In this role, you will lead the development of evaluation tooling that ensures our technology scales safely to millions of people. You will tackle real-world robotics challenges, bridging the gap between simulation and reality to improve everyday lives. Intelligent Agents: Design and deploy "smart" evaluation agents that simulate complex interactions. Intelligent Metrics: Design and deploy advanced algorithms that measure the cognitive performance of the ML models powering our self-driving car’s behavior, utilizing physics-based modeling and machine learning. Close the Learning Loop: Leverage these evaluation frameworks to identify specific behavioral weaknesses in the NuroDriver, driving technical execution to refine the agent's decision-making logic. Define the Technical Archit

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. With Roblox’s daily active users growing at a record pace, we are building the next generation of advertising in an immersive metaverse. Our team sits at the core of the Roblox Ads ecosystem, serving billions of impressions while providing the critical infrastructure that connects global brands with our massive community of creators. We are seeking a Tech Lead Manager (TLM) to drive the technical strategy and lead the execution of the Ads Experience team. This team is responsible for the full spectrum of our monetization experience, including Advertiser Experience (Roblox Ads Manager), Brand Experience (Brand Ads & Integrations), and Publisher Experience (Creator Monetization & Commerce). This is a foundational leadership challenge beyond standard ad-tech. As a TLM, you will be responsible for both the technical vision of our high-scale monetization backbone and the growth and management of a high-performing engineering team. You will pioneer AI integration and balance a three-sided marketplace economy in real-time while fostering a culture of technical excellence. You Will Drive Technical Strategy: Act as the technical authority for the Ads Experience team. Translate ambitious busi

MongoDB is seeking an Engineering Manager to join the Atlas Organization. The organization is responsible for building MongoDB Atlas, our database-as-a-service offering and fastest growing product. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. This includes developing software to interface with the three major cloud providers (AWS, Azure, and GCP) in order to bring security, durability, availability, and performance to all deployments of MongoDB. The Atlas Data Federation & Archiving team is an engineering team responsible for the Atlas capabilities that allow customers to move data from hot to cold storage and run federated queries over that data. The team builds Atlas Data Federation, a distributed query engine that lets users query data across Atlas Clusters and cloud object storage through a unified service. The team also builds Atlas Online Archive which allows customers to move data from Atlas Clusters into fully managed cloud object storage while preserving a seamless query experience across hot and cold datasets. We are forming a new Atlas Data Federation & Archiving team in the Dublin area. The Engineering Manager who fills this position will be pivotal in growing that team. We are looking to speak to candidates who are based in Cork and would like a hybrid or in-office working model. What you’ll do Lead a team of motivated individual contributors who are eager to learn and grow Contribute to the code, design, and architecture of the systems your team develops Work with stakeholders throughout MongoDB to build our roadmap and product offerings Work with customers and support engineers to fix issues and become part of our on-call rotation Collaborate with team members to develop our codebase, best practices, and design principles Foster an inclusive and respectful work environment according to MongoDB's Core Values We’re looking for someone who Has at least 6 years of professi

MongoDB is seeking an Engineering Manager to join the Atlas Organization. The organization is responsible for building MongoDB Atlas, our database-as-a-service offering and fastest growing product. Atlas allows users to deploy fault-tolerant, secure, globally distributed MongoDB clusters in just minutes. This includes developing software to interface with the three major cloud providers (AWS, Azure, and GCP) in order to bring security, durability, availability, and performance to all deployments of MongoDB. The Atlas Data Federation & Archiving team is an engineering team responsible for the Atlas capabilities that allow customers to move data from hot to cold storage and run federated queries over that data. The team builds Atlas Data Federation, a distributed query engine that lets users query data across Atlas Clusters and cloud object storage through a unified service. The team also builds Atlas Online Archive which allows customers to move data from Atlas Clusters into fully managed cloud object storage while preserving a seamless query experience across hot and cold datasets. We are forming a new Atlas Data Federation & Archiving team in the Dublin area. The Engineering Manager who fills this position will be pivotal in growing that team. We are looking to speak to candidates who are based in Dublin and would like a hybrid or in-office working model. What you’ll do Lead a team of motivated individual contributors who are eager to learn and grow Contribute to the code, design, and architecture of the systems your team develops Work with stakeholders throughout MongoDB to build our roadmap and product offerings Work with customers and support engineers to fix issues and become part of our on-call rotation Collaborate with team members to develop our codebase, best practices, and design principles Foster an inclusive and respectful work environment according to MongoDB's Core Values We’re looking for someone who Has at least 6 years of profes

About the Team OpenAI’s Education team is building products that advance how people learn with AI. The team works across higher education institutions, K-12 districts, and country-level partnerships, including applied research on how AI affects learning and cognitive outcomes. The team owns owns ChatGPT Edu, ChatGPT for Teachers, and related product/research work. The team partners closely with go-to-market, research, Consumer Learning, and model teams to turn education-specific insights into product experiences that can improve ChatGPT more broadly. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the Role We’re looking for a hands-on Tech Lead Manager to lead and manage a team of senior full-stack engineers building AI-native learning experiences in ChatGPT. This person will combine technical execution, product judgment, and people leadership: they will write and ship code, manage engineers, and help shape the product direction for how students and Educators use AI. In This Role, You Will Lead and manage a team of three senior full-stack engineers. Build product experiences for ChatGPT Education, ChatGPT for Teachers, and AI-native learning workflows. Partner with research teams on field studies, randomized control trials, classifiers, data pipelines, and cognitive-outcome measurement. Collaborate with Consumer Learning and model teams to translate education insights into broader ChatGPT behavior and product improvements. Drive execution across product, engineering, research, go-to-market, and partner teams. Help define product strategy, priorities, and delivery plans for a new product pod. You Might Thrive In This Role If You Have several years of direct people-management experience with engineers. Are still highly technical and comfortable doing IC engineering work. Have strong pr

About the Team The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will Lead and grow a high-performing Trust & Safety Data Engineering team. Define the roadmap and technical strategy for Trust & Safety data systems. Build canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring. Create reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting,

About the Team Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters. Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale. About the Role We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks. You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training. In this role, you will Design and build a unified dataset read platform for multiple current and future training frameworks. Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable. Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts. Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late

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 talented Tech Lead Manager (TLM) to lead Snowflake’s System Under Test (SUT) team, responsible for evolving how Snowflake engineers test the Snowflake product locally and at scale in CI. The SUT empowers Snowflake engineers by delivering a reliable, low-latency and cost-efficient developer experience across a high-growth, high-demand surface area. As the TLM for SUT, you will lead a small and highly technical team at the intersection of CI, developer infrastructure, and product engineering. You will set direction, drive execution, and partner broadly across Engineering Systems and product teams to deliver a more reliable, faster, and more maintainable test platform for Snowflake’s engineers. In this role, you will: Lead, coach, and grow the SUT team while creating a high-energy, cohesive environment with strong planning, ownership, and career development. Own the roadmap and execution for SUT rollout across development environments, CI and AI workflows. Drive measurable improvements in startup reliability, latency, and cost, using clear SLOs, dashboards, and operational metrics to guide decisions and raise the bar on execution. Serve as the technical anchor for the SUT domain, shaping architecture and guiding the evolution from legacy systems to a composable

AI Tech Lead – Manager Experience- 8-12 years Job Overview: We are seeking a highly experienced AI Tech Lead to design, develop, and deliver scalable AI-driven applications while leading cross-functional teams. The role involves end-to-end ownership of AI solutions, including architecture design, deployment, and optimization, ensuring alignment with business objectives. The candidate will collaborate with stakeholders, data engineering teams, and product management to build enterprise-grade AI systems leveraging modern cloud and AI technologies. Key Responsibilities / (Person Specifications): Lead implementation and delivery of AI applications across teams. Design end-to-end AI architectures integrating open-source and enterprise tools. Translate business requirements into scalable AI solutions. Define architecture roadmaps and best practices. Build data pipelines, CI/CD, and monitoring systems. Deploy scalable systems using Docker and Kubernetes. Ensure performance, scalability, and security. Mentor teams and drive knowledge sharing. Key Skills / Job Specifications (Mandatory): AI frameworks: LangGraph, AutoGen, CrewAI. Strong Python with TensorFlow, PyTorch, Keras. Knowledge of NLP & Deep Learning (RNN, CNN, LSTM, Transformers). Cloud platforms: AWS / Azure / GCP. Docker, Kubernetes, CI/CD tools. Terraform / CloudFormation (IaC). SQL & NoSQL databases. Distributed systems, REST APIs, GraphQL, microservices.