Jobs at Sigma Computing

Manage a high-volume portfolio of mid-market SaaS customers using scalable engagement, automation, onboarding, and customer education. Monitor product adoption and health signals to mitigate churn, identify expansion opportunities, and drive renewals. Analyze cohorts and customer usage data, create targeted communications, lead outcome-focused meetings, and develop reusable playbooks. Collaborate with Sales, Support, and Product to resolve issues and improve customer outcomes.

Owns Sigma’s end-to-end sales compensation administration, including commission calculations, payout validation, quota and crediting mechanics, reporting, automation, controls, and audit readiness. The role partners with Finance, Revenue Operations, People, Payroll, Legal, and Data to resolve disputes, prevent payment errors, support accounting close, and improve seller visibility. Requires strong sales compensation, data validation, systems, and cross-functional influence skills, with experience in SaaS and consumption-based models preferred.

Build and maintain scalable security platforms, automation, APIs, detections, and internal tooling for a cloud-native SaaS environment. Secure AI applications, LLM services, identities, SaaS platforms, cloud infrastructure, and APIs. Develop controls against prompt injection, data leakage, model misuse, and excessive permissions while supporting vulnerability management, incident response, threat modeling, and security operations.

Technical Writing Interns will test and document product features, create tutorials, examples, release notes, and visual content, and improve documentation for users and AI agents. They will collaborate with engineers, designers, product managers, and writers; participate in planning and feature testing; publish content through a docs-as-code workflow; analyze customer feedback and metrics; and own a documentation project from ideation through implementation.

Build, prototype, test, and deploy production software features for Sigma’s cloud analytics platform. Interns collaborate with engineers, product managers, designers, and users; develop scalable frontend or backend systems; optimize performance; create automated unit tests; document work; and use customer metrics to improve product decisions. The role includes owning a development project from ideation through implementation while working full-time in person for 12 weeks.

Conduct original AI/ML research across search, recommendations, NLP, and agentic workflows. Prototype and productionize AI systems, address AI and analytics UX challenges, and contribute to scalable infrastructure for model experimentation, training, and evaluation. The role requires a current AI/ML PhD student with strong machine learning knowledge and an understanding of the end-to-end ML lifecycle, including data curation, training, deployment, and monitoring.

Lead the commercial and scaled Customer Success organization, developing enterprise retention and growth strategy, managing CSM teams, driving customer value and product adoption, and improving customer health across the lifecycle. The role owns NDR and MBO performance, builds customer advocacy, establishes cross-functional feedback loops, and leads change and operational scaling across the post-sales organization.

Leads a team of Support Engineers serving enterprise data-platform customers. Responsibilities include hiring, coaching, escalation management, support strategy, cross-functional collaboration, process improvement, and performance against CSAT, SLA, response, and resolution metrics. The manager will analyze support data, improve customer experience and operational efficiency, and maintain technical expertise in databases, business intelligence, SQL, data modeling, and cloud data warehouses.

Leads and coaches a Commercial Solution Engineering team while remaining hands-on in discovery calls, demos, roadmap presentations, customer engagements, and executive meetings. Partners with Sales, Customer Success, Product, Marketing, and channel teams to grow revenue. Oversees forecasting, deal strategy, hiring, capacity planning, performance management, technical responses, and team objectives while ensuring high-quality consultative selling and customer-focused solutions.

Manage high-value SaaS customer accounts, build relationships with decision-makers, and improve net dollar retention through adoption, upselling, cross-selling, and churn reduction. Use analytics and business intelligence expertise to guide customers, develop success plans, advocate for product improvements, and deliver training, webinars, and workshops. Partner with customers to align the platform with business goals and drive measurable value.

Design and maintain production data pipelines and architecture across Snowflake and Databricks, scale Terraform deployments, implement data governance, build demo data processes, and collaborate cross-functionally to support analytics and product use cases.

Build and maintain scalable security platforms, automation, and tooling to protect data across SaaS, cloud, endpoints, collaboration tools, AI systems, and data warehouses. Develop data discovery, classification, governance, DLP, DSPM/SSPM, insider-risk, and access controls; leverage AI and automation to improve detection, prevention, and incident workflows while partnering with cross-functional teams.

Sell Sigma's analytics platform to new customers in the Bay Area. Manage the full sales cycle, generate pipeline, maintain Salesforce records, collaborate with partners, and meet quota. Engage consultatively with data and analytics stakeholders to close deals and build customer advocates.

Design and implement backend distributed services and modern APIs to support a cloud application. Build and deploy robust, secure web applications, triage and resolve production issues, optimize SQL and database internals, and collaborate through design and code reviews using tools like Rust, Go, GraphQL, Node, and Kubernetes.

Build and maintain compiler infrastructure that translates spreadsheet interactions into optimized SQL for cloud data warehouses. Design intermediate representations and apply query optimization strategies, contribute to backend (Rust) and frontend (TypeScript) foundations, debug complex issues, and collaborate with engineers and product stakeholders to drive architecture and feature development.

Design, prototype, and productionize AI systems and infrastructure—recommendations, natural language interfaces, agentic workflows—partnering with product and engineering to scale ML across the full lifecycle (data curation, training, deployment, monitoring).

Sell Sigma's analytics platform to mid-market digital-native accounts in the Bay Area. Manage full sales cycle from prospecting to close, perform deep account planning, maintain Salesforce pipeline and forecasts, run value-based discovery, collaborate with partners, and travel (~25%) for onsite meetings to drive new revenue and customer advocacy.

Sell Sigma's data and analytics platform by owning the full sales cycle, generating pipeline, managing forecasts in Salesforce, engaging partners, closing new customers, and developing customer advocates in the BI market.

Build and optimize high-performance interactive analytics features on modern data warehouses. Design and implement full-stack features, develop performance-improving algorithms, triage and debug system issues, and collaborate across infrastructure, product, design, and customer teams to support rapid user growth.

Act as technical presales advisor for Sigma's analytics platform: run discovery sessions, build and present customized demos and prototypes, support RFP/RFI responses, advise on integrations and data migration, manage multiple customer engagements, and meet quarterly and annual objectives in partnership with sales and product teams.