Ai And Cloud Service Provider Account Executive in San Francisco

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

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 Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. 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 developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and contai

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 the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

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 eval 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 support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. 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 design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

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 eval 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 support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. 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 design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About The Role & Team Amplitude is only as useful as the data inside it. The Data Warehouse and Integrations team owns how that data gets in and out — importing behavioral and customer data from cloud data warehouses like Snowflake, Databricks, and BigQuery, from cloud object storage like S3 and Azure Blob Storage, and pushing enriched event data back out to warehouses, object storage, streaming destinations, and downstream advertising and marketing platforms. That means batch and streaming pipelines moving billions of events a day, connections that have to keep working across dozens of customer-controlled systems, credentials and configuration that have to stay correct and secure, and latency and reliability targets that customers build their own pipelines on top of. Recent work includes launching new warehouse export destinations, migrating our import

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

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Team DevX owns engineering velocity at Amplitude: build systems, CI/CD, developer environments, and internal tooling. We're building a software factory: automated workflows that remove manual bottlenecks from how engineers ship code. The Role We're looking for a Staff Software Engineer – DevX (Hybrid – San Francisco) who bridges infrastructure and application thinking and can accelerate how the whole team develops, tests, and ships in the cloud. You'll set architecture for our developer platform, lead our software factory work, and push our development model toward cloud-first workflows. This is a high-leverage, low-oversight role. You'll own initiatives end to end, from an ambiguous problem to production, and set technical direction for a foundational team. What You'll Do Cloud development platform: Unify and scale our existing loca

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Role & Team We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses. Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results. Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments. This is not a traditional data engineering management ro

The Sigma Commercial Solutions Engineer believes in the power of analytics to transform organizations and uncover new data insights to increase business agility. The Sigma Solutions Engineer will act as the trusted advisor to our prospects and customers working in tandem with Sales, Business Development, Product Management, Customer Success, and Support. This individual is ultimately responsible for managing and delivering on all activities related to the technical presales cycle. This includes presentations, demonstrations, and hands on development of prototypes. You will align closely with our Commercial Sales Representatives focused on sales in new and existing accounts. What You Will Be Doing Understand and uncover business challenges and issues faced by the customer and be able to run targeted discovery sessions or workshops Engage with business users to define, create, and showcase solution prototypes Build and present customized demos for customers, trade shows, and webinars Confidently present and articulate the business value of the Sigma platform to all levels within an organization Deliver product, technical, and security related responses to RFPs/RFIs Participate in product, sales, and relevant technology certifications to acquire, maintain, and grow skill sets Work as a team player by contributing, learning, and sharing new knowledge Be conversant in integration and data migration approaches to help customers develop their data lifecycle and analytics strategy with Sigma Manage multiple customer engagements concurrently Attain quarterly and annual objectives assigned by management Become a Sigma champion and product expert; prospects and customers will look to you for advice and expertise Qualifications We Need Minimum 2 years of analytics, business intelligence, or sales engineering experience Customer relationship skills Strong understanding of database concepts Understanding of advanced spreadsheet concepts Cloud

Role Overview We are seeking a Staff Simulation Engineer to build an end-to-end aerial autonomy simulation stack at DoorDash Labs. This is a highly technical, hands-on leadership role focused on defining and implementing the simulation architecture that underpins autonomy development, validation, CI/CD testing, and pilot training. You will operate as the technical authority for simulation: owning core architecture decisions, developing key components yourself, and setting engineering standards. You will build and mentor a small, high-caliber simulation team while remaining deeply involved in implementation and system design. This role is ideal for someone who has built simulation systems from first principles, understands simulator internals deeply, and is excited to create a world-class platform from scratch. Key Responsibilities Architect and implement an end-to-end simulation stack for aerial autonomy at DoorDash Labs.. Develop high-fidelity simulation capabilities, including: Flight dynamics modeling Contact modeling and constraint handling Sensor and perception simulation Autonomy software-in-the-loop (SITL) integration Design and implement scalable simulation infrastructure to support: Regression testing in CI/CD pipelines Continuous validation of flight autonomy and autopilot software stack Mission-level testing and scenario generation Build cloud-deployed simulation systems to enable large-scale parallel testing and pilot training. Partner closely with autonomy, controls, and aircraft teams to ensure simulation fidelity and validation alignment. Establish technical direction, architecture standards, and performance benchmarks for simulation. Mentor and grow a small team of simulation engineers while remaining deeply hands-on. Required Qualifications Master’s or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, or a related field. 10+ years of experience in robotics or physics-based simulation. Deep expe

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor