7+ years in solutions architecture, software engineering, or technical consulting, preferably in AI, data, or SaaS
Proven track record of building and shipping solutions, not just designing them
Deep fluency with AI-assisted development tools like Cursor, Copilot, and Replit
Strong understanding of LLM application patterns including RAG and prompt engineering
Excellent engineering judgment to balance speed and production readiness
Ability to clearly present technical work to both technical and non-technical stakeholders
Demonstrated autonomy and leadership in a less structured environment
Responsibilities
Lead the technical build for early client engagements, delivering prototypes quickly
Design and implement tailored AI solutions from discovery to go-live
Create live demos and proof-of-concepts to support sales efforts
Ensure technical quality across all solutions, focusing on security and scalability
Transition delivered solutions to production, managing monitoring and support
Apply responsible AI standards throughout the delivery process
Document architecture patterns and establish quality standards for AI implementations
Benefits
Opportunity to shape the AI Professional Services practice from the ground up
Potential to grow into a Tech Lead role as the team expands
Collaborative work environment with cross-functional teams
Chance to influence product roadmaps based on client insights
Access to cutting-edge AI tools and technologies
Involvement in creating repeatable service offerings and methodologies
Full Job Description
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
