Principal Solutions Architect

What success looks like

Within your first 6–12 months

• Strategic deals have clearer technical feasibility, integration scope, risk, and effort estimates before SOW.
• FDE teams move faster because they have stronger architecture guidance, launch gates, and reusable implementation assets.
• Complex deployments launch with better observability, evals, fallbacks, and privacy controls.
• Customers trust Maven’s technical direction in security, architecture, and executive-level reviews.
• Repeated deployment patterns become productized rather than remaining bespoke.

What makes you a fit

Required

• 7+ years in Solutions Architecture, Applied Engineering, Forward Deployed Engineering, Sales Engineering, or equivalent customer-facing technical leadership for enterprise SaaS, data, ML, or AI products.
• Track record taking complex enterprise technical solutions from discovery or POC into production.
• Strong system design skills across APIs, event-driven systems, data modeling, identity/consent flows, latency, throughput, reliability, and observability.
• Practical AI/LLM depth: RAG, tool use/function calling, prompt and retrieval evaluation, safety guardrails, agent orchestration, and quality measurement.
• Hands-on technical fluency in TypeScript/Node, Python, or similar. You are not the primary production engineer, but you can prototype, review code, debug integrations, and reason through implementation trade-offs.
• Excellent written, verbal, and visual communication. You can lead a security review, produce a clear architecture diagram, and present trade-offs to executives.
• Builder mindset. You want to help create the Solutions Architecture function, not just operate inside an existing one.

Nice to have

• Contact center / CCaaS experience with platforms like Genesys, Five9, NICE, Twilio, or Amazon Connect.
• Depth with Zendesk, Salesforce Service Cloud, ServiceNow, or similar customer support systems.
• Experience in regulated or complex data environments such as financial services, healthcare, gaming, marketplaces, or franchise businesses.
• Experience at a frontier AI company, FDE-style company, data/ML platform company, high-growth SaaS company, or as a technical lead on complex enterprise AI programs.
• Prior experience building a technical function from zero to one.