[Hiring] Lead Solutions Architect @Foundever®

Role Description

We are building an AI Professional Services practice from the ground up. We need a technically savvy Lead Architect who can own the build end-to-end: from client brief to working prototype, from prototype to production, and from solo contributor to the technical anchor of a growing team. This is a rare founding opportunity. You will personally ship the first solutions, establish what great AI delivery looks like at Foundever, and grow into a Tech Lead role as the practice scales. You will work closely with Sales, Product, and client stakeholders — bringing engineering credibility and realistic delivery judgment to every engagement.

WHAT YOU'LL DO

• Client Delivery & Technical Build
  • Be the primary builder in every early client engagement — take a scoped brief to a working prototype within days, not weeks.
  • Design and deliver tailored AI solutions using LLMs, agents, RAG pipelines, and AI-assisted development workflows — from discovery through go-live.
  • Build live demos and proof-of-concepts that directly support deal closure, working alongside commercial stakeholders.
  • Own technical quality across all solutions: security, scalability, maintainability, and production readiness.
  • Lead the transition of delivered solutions to production — including monitoring, cost control, reliability, and support handoff.
  • Apply responsible AI delivery standards: data privacy, model selection, prompt and version management, and safeguards where required.
• Commercial & Scoping Judgment
  • Assess client needs and determine the best solution path: EverSuite capability, off-the-shelf tooling, or custom AI build.
  • Estimate build costs with precision — time, infrastructure, tooling, and ongoing maintenance.
  • Join client scoping sessions and technical discovery calls, bringing engineering credibility and realistic timelines.
  • Flag reusable solution patterns that can evolve into packaged service offerings.
  • Partner with Sales to scope, price, and validate new services opportunities from a technical standpoint.
• Product Feedback Loop
  • Identify recurring custom client requests that signal mid-term product opportunities.
  • Communicate technical insights clearly and actionably to Product Managers.
  • Define what "productizable" looks like technically — providing the feasibility foundation for roadmap decisions.
  • Feed client insights back into the EverSuite roadmap through structured cross-functional collaboration.
• Practice Building
  • Document architecture patterns, reusable components, and build playbooks from day one.
  • Establish delivery methodologies and quality standards for AI implementations.
  • Create repeatable offerings: AI discovery workshops, rapid prototyping packages, paid pilots, and managed AI solution support.
  • As the team grows, step into a Tech Lead role — setting technical standards, reviewing work, and mentoring junior architects and engineers.
  • Define technical hiring criteria for future team members.

Qualifications

• 7+ years in solutions architecture, software engineering, or technical consulting — ideally in an AI, data, or SaaS context.
• Strong hands-on track record building and shipping solutions — not just designing them.
• Deep fluency with AI-assisted development workflows (Cursor, Copilot, Claude, v0, Replit, etc.) — you build with these tools daily.
• Solid understanding of LLM application patterns: RAG, agents, prompt engineering, tool use, and fine-tuning.
• Strong engineering judgment — you know when to move fast and when production readiness requires slowing down.
• Ability to present your own work clearly to both technical teams and non-technical client stakeholders.
• Proven ability to estimate, scope, and defend technical build decisions commercially.
• Demonstrated ability to operate autonomously and lead without a fully formed team around you.

Requirements

• Background in enterprise software, cloud platforms, or AI/ML infrastructure.
• Experience in a startup, scale-up, or zero-to-one environment — comfortable building without a playbook.
• Familiarity with MLOps, vector databases, or AI safety considerations.
• Prior experience influencing a product roadmap from field or client insights.
• Exposure to P&L ownership, SOW management, or professional services revenue models.
• Background in BPO, CX, or contact center technology.
• Experience in regulated industries where responsible AI is non-negotiable.

Benefits