Sigma Computing FDE

Solution Architect

  • Location San Francisco, CA
  • Seniority senior
  • Posted 2026-06-03

Original posting ↗ You apply on the company site — we never collect applications.

Extracted automatically from public job postings. Always verify details on the original posting before applying.

role details

Partner with SEs on complex enterprise deals, architecting solutions and leading technical conversations.

Summary generated by AI from the original posting.

Hard requirements to check first

  • Clearance:not mentioned in the posting
  • Work auth:not mentioned in the posting
  • Travel:customer-facing; travel not stated

Skills

DatabricksSnowflakeAgentsMCPAIChatGPTCursorSigma AssistantLLM enrichmentMCP integrationWarehouse-native agent patternsClaude

Excerpt from the original posting

 

 

Solution Architect 

Sigma Computing

The SA role has evolved. Here’s the version we’re hiring for. 

The SA job in 2026 is not the SA job in 2023. Three things now sit at the center of how we evaluate this role. This hire has to do all three at a senior level, with the architectural depth to back it up.

1. Use AI every day to do the job better. 

If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are. We expect this hire to treat AI tooling as default infrastructure, not novelty. Come with a point of view on what you run, why, and how you use it to compress weeks of work into days.

2. Sell AI into the account. 

Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what. You have to be fluent. You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns. You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call. You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs.

3. Sell against AI. 

Every enterprise deal has AI competition in it. Sometimes it is Databricks Genie. Sometimes it is Snowflake Cortex Analyst. Sometimes it is a systems integrator pitching a bespoke agent built over the weekend. You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving. You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls.

About Sigma 

Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, and analytics directly in Sigma, with governance and security inherited from the cloud data warehouse. No extracts, no separate AI pipelines, no shadow stack to maintain.

About the role 

Solution Architects are the senior technical voice on our Solution Engineering team. SAs partner with SEs on the most complex enterprise deals: architecting solutions, leading deep technical conversations, and unblocking opportunities that hinge on data infrastructure, security, or AI strategy…

→ Sigma Computing · Greenhouse

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