Hr Workforce Technology Manager in San Francisco

About the Role Sigma is transforming how businesses run by delivering a high performance platform on the modern data architecture. Hence, we are growing the engineering team and looking for engineers who are excited to solve challenging problems, deliver impactful capabilities throughout our stack to build world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible for all users. What You Will Be Doing Solve challenging problems that arise in providing an interactive experience on data warehouses for data exploration and analysis Build with modern tools and languages like Rust, Go, GraphQL, Node, and Kubernetes Build backend distributed services, new algorithms and modern API to support a cloud application Triage product or system issues and debug/track/resolve by analyzing the sources of issues Design and implement new software features to support our fast growing user base Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies Qualifications We Need 5+ years industry experience building and maintaining high-quality software Experience building and deploying robust and secure web applications in a continuous deployment environment Desire to be a great teammate and have fun at work without compromising ownership towards your work Strong sense of craftsmanship, and a healthy academic curiosity to solve challenges at sigma Strong Computer Science fundamentals Qualifications We Want (also, skills you’ll learn!) Data driven aptitude and its application to solve distributed system problems Data model design, and API development experience SQL query optimization and database internals Administered cloud service infrastructure (GCP, AWS, Azure) Prior experience working at high growth company solving technical problems to enable continued success Additional Job details The base salary range for this position is $170k - $240

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable’s infrastructure is evolving to meet the needs of our fast growing engineering org. We are looking for infrastructure engineers to join our team to help improve critical product infrastructure, with a focus on building systems that have a great developer experience and will scale as we grow. We currently have openings on: Asynchronous Serving: The Asynchronous Serving team is scaling critical systems used by Airtable’s most essential and up-and-coming product features, especially AI features. Upcoming projects include refactoring our background task queue to track its tasks in DynamoDB, adding quality of service to the job queue, and revamping a streaming service to handle 10x scale while being more resilient. Compute: The compute pod builds and manages our Kubernetes-based platform that supports every service at Airtable, including all new AI services such as vector databases, AI evals store, and document extraction and understanding services. We have a lot of exciting foundational work in our roadmap, such as Overhauling our network stack and service discovery, to simplify service setup and strengthen security Region level disaster recovery, and bringing up compute platform from 0->1 in a new region Building custom Kubernetes operators for reliably managing some of our most critical workloads Developer Platform : The Developer Platform team sits at the intersection of all engineering at Airtable, focusing on building the internal tooling, frameworks, and CI/CD systems that power our product teams. We strive to streamline developer workflows - from build and test cycles to production deployments—and foster a best-in-class developer experience. Join us if you’re passionate about creating high-lever

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable’s mission is to bring the power of computing and software development to everyone. We are developing a powerful and extensible toolkit that our customers can leverage to solve a variety of different problems and workflows. We’ve seen our most sophisticated customers use the product to run global processes across thousands of employees, coordinate precision manufacturing pipelines, and consolidate previously siloed mission-critical data into a single source of truth. The complexity of these use cases requires us to be extremely thoughtful about how we design and implement new functionality in the product and make sure it’s both easy to use and comprehend for our customers and maintainable for us. As a Full-Stack, Backend engineer at Airtable, you will have the opportunity to work with customers to deeply understand their needs and workflows. You will collaborate with cross-functional partners across product management, design, research and data science to create innovative new features that enable our customers to do their best work. You will be responsible for owning and executing the end-to-end implementation of these new features that will contribute to making our toolkit even more powerful and successful. We currently have openings on: The Admin & Governance Team (Full-Stack/BE) ensures Airtable is secure, compliant, and enterprise-ready. It owns key admin capabilities like the Admin Panel, SSO, and audit systems, as well as foundational features like User Groups. This team's mission is to accelerate organizational value for the largest customers with enterprise-first governance and controls. The Omni Capability & Quality Team (Full-Stack/BE) brings the power of AI directly to Airtable end users—

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. At Airtable, we're passionate about democratizing software creation — empowering anyone to build powerful, flexible tools without writing code. With our shift to an AI-native platform, customers can now generate full apps and deploy AI agents directly into their workflows. Data engineering plays a critical role in this evolution by delivering the insights our teams rely on to improve user experience, measure agent impact, and understand how the business is performing at scale. As a Software Engineer, Data at Airtable, you'll make an enormous contribution to our data engineering efforts. You'll design and own mission-critical data pipelines to enable decision-making, partner with company leaders to create scalable data solutions, and launch innovative alerting and visualization solutions. The Team Our team is embedded in how Airtable understands itself as a business, working closely with Data Science and Analytics. What's unusual here: the platform you're instrumenting is the same one your customers use every day. When Airtable ships a new AI agent capability, you're among the first to wire it up, measure its adoption, and influence what gets built next. Product & AI Data Infrastructure This team builds and owns the foundational data pipelines that power product analytics across Airtable. As Airtable shifts to an AI-native platform, our work increasingly involves instrumenting and measuring AI product usage, building event pipelines for AI agents, surfacing AI-native adoption metrics in core business tables, and developing AI-powered data discovery tooling, including vector search over our catalog metadata. We partner closely with product analytics, product engineering, and data infrastructure to turn business question

You will: Manage the growth program from end to end, including top-of-the-funnel growth / recruiting campaigns, applications processing, and hiring and onboarding Represent and champion the brand, promoting its value proposition to candidates and stakeholders, driving engagement, and taking ownership of process improvements that streamline growth pipelines and support program success Optimize full growth funnel for conversion and experience Build and lead new growth recruiting campaigns and channels to meet business goals Be the subject matter expert for all recruiting systems (ATS: Greenhouse), tools, and processes, and provide training/onboarding as needed Own internal reporting and analytics, and keeping all the internal hiring data clean and up-to-date in our systems Be the strategic driver behind on impactful initiatives to improve the workflow, data infrastructure and reporting Proactively flag discrepancies in hiring plans, interview process, JDs, offer details, etc. and maintain data integrity and operational excellence within the team Work from the San Francisco office, with occasional travel for onsite growth events. Ideally you’d have: Minimum of 3-7 years of experience working in Growth, Recruiting or RecOps at a rapidly growing company Extensive experience using Greenhouse as a Site Admin (user permissions, approvals, custom options) and pulling ad hoc reports using our internal TA tools (report connector, reporting capabilities, and limitations) Strong knowledge of Gsuite (VLOOKUP, pivot tables, data validation, conditional statements and formatting, filters, etc.) Excellent written and verbal communication skills, with the ability to tailor messaging to diverse audiences Must have a deep understanding of Growth / Recruiting Pipelines, Funnels and Conversion metrics Demonstrated excellent project management skills, ability to pull and manipulate data sets, critically analyze existing processes, and identify opportunities for process improvement Able to

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in

About Prophecy Prophecy is building the next generation AI-powered data prep and analysis platform. Our platform enables business analysts and data teams to transform raw data into reliable, production-ready datasets and insights faster, using modern data infrastructure and AI-driven capabilities. We work with leading enterprises to simplify how organizations prepare, analyze, and operationalize data, while maintaining strong governance, security, and operational control. Our mission is to make it dramatically easier for organizations to turn complex data into trusted insights that drive decisions. About the Roles We are looking for a Director of Strategic Partnerships who can do both: drive revenue through Prophecy's partner ecosystem, and build an effective partner program. This is an early-stage, high-ownership motion, the playbook is still being written, and you'll have real influence over how we engage partners, what good looks like for partner-sourced pipeline, and how we build durable co-sell relationships with Snowflake, Databricks, GCP field and partner teams. You will sit at the intersection of sales, partnerships, and strategy, owning partner performance while building the programs and processes that scale it. You'll work directly with our AEs and SEs to bring partners into deals at the right moments, and you'll serve as the primary point of contact for our strategic cloud and ecosystem partners. What You’ll Own Partner Revenue & Pipeline Own and exceed partner-sourced and partner-influenced revenue targets on a quarterly basis Proactively generate pipeline through Snowflake, Databricks, and GCP field AEs and PDMs — building the relationships that produce qualified, sourced opportunities Drive joint account mapping and target account activation against Prophecy's ICP: enterprises running Alteryx on Snowflake or Databricks Activate co-sell motions through marketplace programs (GCP Marketplace, Snowflake Partner Network, Databricks

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 7+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval

About Scale AI At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries fo

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data

Director of Engineering, Physical AI Role Overview The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment. This role requires significant ownership in a fast-paced environment and you will motivate internal teams to set the pace for business growth. Travel will come into play. Key Responsibilities: Set and drive the technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research Lead a multidisciplinary engineering organization—spanning engineering managers, software engineers, ML engineers, and ML research scientists—while designing the organizational structure, talent strategy, and culture required to scale rapidly without compromising on quality or strategic alignment Maintain exceptional technical and operational excellence by deeply understanding team deliverables, asking incisive questions, identifying slipping standards early, and knowing precisely when to step in Drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities Collaborate with researchers and clients to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads Required Qualifications: Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field 8+ years of engineering experience in fast-paced environments, including 4+ years direct people management demonstrated history of recruiting, mentorin

At Scale, we believe that AI will dramatically improve the world, and our mission is to accelerate the development of AI. We’re looking for a Field Marketing and Events leader to continue to build and manage Scale’s robust Gen AI and Research field marketing and events program, including but not limited to Scale hosted executive events, Scale hosted practitioner events and meetups, research conferences, and our annual flagship conference, AI Leadership Summit. You will join a rapidly growing team with the opportunity to manage and execute events from start to finish, drive lead generation and pipeline growth, and plan event programming with the largest names in AI. The successful candidate will have a solid understanding of technology, model builder, and research markets, strong project management skills, a strategic mindset, ability to manage and grow a team, and a passion for AI & technology. You will: Own annual planning for all Gen AI and Research events including strategy and budget Establish event activities in line with sales goals and deal acceleration, prioritizing goals from the go-to-market leadership and business development teams on event location and audience Manage team of field marketing and events managers who will execute on planning and logistics. This role should have a player-coach mentality and ability to also execute on nuts to bolts planning for all executive dinners, meetups, happy hours, sponsored trade shows, and hosted conferences Manage contractor relationships including event production firms and outside vendors, and event budgets Align with growth marketing on marketing campaigns and marketing qualified lead (MQL) reporting Track event campaign performance, measuring ROI, results, and metrics through Salesforce and own any course correction for events that are not performing Own all aspects of Scale hosted conference, Scale AI Base Camp, including venue selection, vendor management, logistics, speaker