Solution Architect

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 compe [... source excerpt omitted ...] 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 w [... source excerpt omitted ...] tterns, 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. Mentor SEs. Contribute to the wiki, the playbooks, and the next hire’s ramp. Manage several enterprise engagements at once. Earn and maintain product, sales, and technology certifications. Hit quarterly and annual targets set by your manager. What we’re looking for Technical depth. 8+ years in business intelligence, analytics engineering, or data platform roles, with at least 3 in a