Lead Solutions Architect, AI Build & Delivery (Remote, Any Location, US)
# Lead Solutions Architect, AI Build & Delivery (Remote, Any Location, US) **Foundever** · United States · `Remote` · `Full Time` 💼 **Уровень роли:** `Senior` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Himalayas (JSON API)* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[Solutions-Architect]` `[AI-Architect]` `[Technical-Architect]` `[Software-Architect]` `[AI-Engineer]` `[Principal-AI-Solutions-Architect]` `[AI-Solutions-Architect]` `[AI-Solution-Architect]` `[Enterprise-AI-Solutions-Architect]` `[Senior-AI-Architect]` `[AI-Solutions-Lead]` `[Data-and-AI-Solution-Architect]` `[AI-ML-Solutions-Architect]` --- ### About the Role About Foundever : Foundever ™ is a global leader in the customer experience (CX) industry. With 170,000 associates across the globe, we are the team behind the best experiences for +750 of the world’s leading and digital-first brands. Our innovative CX solutions, technology and expertise are designed to support the operational needs of our clients and deliver a seamless experience to customers in the moments that matter. Job Summary We are building an AI Professional Services practice from the ground up. We need a technically savy 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 1. 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 2. 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 3. 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 4. 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 WHAT WE'RE LOOKING FOR Must-Haves - 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 Nice-to-Haves - 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 WHAT "AI BUILD FLUENCY" MEANS HERE This isn't an architecture-on-paper role. We expect our Lead Architect to personally ship working software — not just produce diagrams and hand off to others. You use AI-assisted development tools as a force multiplier, not a crutch. You review AI-generated code critically, make real-time architecture decisions without committee alignment, and have a clear point of view on where these tools accelerate delivery and where they introduce risk. You should be able to demonstrate all of the following: - Spin up a working prototype within hours of a client brief - Critically review AI-generated code — not just prompt and ship - Make real-time architecture decisions without waiting for committee sign-off - Scaffold, ship, and iterate on real solutions under commercial pressure - Coach clients on integrating AI-assisted workflows into their development culture - Maintain engineering rigor around security, scalability, and maintainability Originally posted on Himalayas
- Solutions-Architect
- AI-Architect
- Technical-Architect
- Software-Architect
- AI-Engineer
- Principal-AI-Solutions-Architect
- AI-Solutions-Architect
- AI-Solution-Architect
- Enterprise-AI-Solutions-Architect
- Senior-AI-Architect
- AI-Solutions-Lead
- Data-and-AI-Solution-Architect
- AI-ML-Solutions-Architect
Наблюдалась 2026-10-12, впервые 2026-10-12, источник — Himalayas (JSON API).