Solution Architect

We Love AI Jobs; San Francisco (CA); On-site; USD 135,000 - 180,000; Full time

Job summary

Sigma Computing's Solution Architect role is a senior technical voice on the Solution Engineering team. You will lead architecture discussions, run deep discovery, and craft prototypes that prove value in data infrastructure, security, and AI strategy.

You will partner with Sales, Product, Engineering, and Support to advance deals, architect Sigma agents and MCP integrations, and articulate the AI runtime story to CTOs and CISOs across complex enterprise accounts. On-site in San Francisco.

Qualifications

• 8+ years enterprise solution architecture experience.
• Bachelor’s degree or equivalent experience.
• Experience with data infrastructures and AI strategy.

Responsibilities

• Lead technical strategy, discovery, and architecture workshops for enterprise opportunities.
• Design and build prototypes proving value with AI and Sigma patterns.
• Advise on governance, integration, and patterns across major data platforms.

Skills

SQL

Snowflake

Databricks

BigQuery

Redshift

dbt

Fivetran

MCP

Education

Bachelor’s degree or equivalent experience

Tools

Claude

ChatGPT

Cursor

Gemini

Sigma Assistant

MCP

Job description

# Solution ArchitectSigmaSan Francisco, CAFull-time$135,000 – $180,000 / yearAI tools:ClaudeChatGPTCursorGeminiSigma AssistantMCPUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageYou’ll lead technical strategy for complex enterprise opportunities, helping customers design Sigma solutions involving data infrastructure, security, and AI. The role combines architecture workshops and prototypes with sales support, competitive positioning, reusable team resources, and product feedback.* Permanent* On-site* 8+ years* Bachelor’s degree or equivalent experience### Skills and expertiseSQLSnowflakeDatabricksBigQueryRedshiftdbtFivetranMCP### Key responsibilities* Lead technical strategy, discovery, and architecture workshops for complex enterprise opportunities.* Build prototypes and explain Sigma AI and warehouse-agent patterns to customer stakeholders.* Develop reusable architecture and sales resources, and advise Product and Engineering on customer needs.## How this job comparesCompared with 417 open senior customer success jobs on October 10, 2026.Pay: This job pays $135K to $180K a year. The 164 open senior customer success jobs that publish US pay start at $135K on average, so this job starts in line with them.Similar open jobs: We Love AI Jobs lists 417 open senior customer success jobs at 145 companies.Remote work: This job is on site. 144 of the 417 senior customer success jobs (35%) are remote.AI in this role: Medium. The role uses AI tools and works with AI systems as a regular part of the job. The posting explicitly expects daily use of AI tools and regular customer work on agents, MCP integrations, and Sigma’s AI features. The role architects and sells AI-enabled solutions rather than building or training models.## Full descriptionSolution ArchitectSigma ComputingThe 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 SigmaSigma 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 roleSolution 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. Your depth compounds the work SEs are already doing and accelerates deal velocity across the territory.You will work alongside Enterprise Regional Sales Managers and SEs on new and existing accounts. You will partner closely with Sales, Product, Engineering, and Support. Prospects and customers will come to you for architectural guidance and product expertise, especially on AI strategy, governance, and warehouse-native architecture.What you’ll do• Lead the technical strategy on complex enterprise opportunities, paired with the SE assigned to the account.• Run deep technical discovery and architecture workshops with data teams, security teams, AI leads, and executive stakeholders.• Design and build custom prototypes that prove out high-value use cases, including AI-driven workflows using Sigma Assistant, Sigma agents, warehouse agents, and MCP integrations.• Present Sigma’s architecture and AI runtime story to audiences ranging from analysts to CTOs and CDOs.• Own the technical narrative on RFPs, RFIs, AI risk reviews, and security questionnaires.• Advise on integration, migration, governance, and AI patterns across Snowflake, Databricks, BigQuery, and Redshift.• Position Sigma against Databricks AI/BI and Genie, Snowflake Cortex Analyst, Tableau, Power BI, Looker, and AI-native entrants. Defend that position with architecture, not slogans.• Build reusable SA assets: architecture patterns, AI-workflow playbooks, competitive teardowns, and reference implementations the whole team can run.• Shape the product from the front line. File feature requests, write up customer patterns, and partner with Product and Engineering on what to build next, especially across the AI surface.