Designs and oversees reusable agentic AI architectures for client engagements. Translates business problems into technical requirements, evaluates build-versus-buy decisions, establishes orchestration and human-in-the-loop controls, and guides nearshore engineering teams. The role also identifies reusable intellectual property, supports client growth, and communicates ROI, margins, and technical risk to executives and consulting partners.
Role Overview
CodeRoad is seeking a strategic AI Solutions Architect to serve as the technical bridge between our boutique consulting partners and our execution engines. This is a "boots on the ground" role for a business-minded technologist who can navigate complex client environments to design, validate, and oversee the implementation of agentic AI systems.
Your mandate is to ensure that every client engagement moves CodeRoad closer to non-linear scale by prioritizing reusability, modularity, and IP creation over bespoke labor.
Core Responsibilities
- Strategic Client Translation: Lead deep-dive discovery sessions at customer sites to translate ambiguous business problems into structured agentic workflows and technical requirements.
- Agentic Architecture Design: Design high-level architectures for autonomous agent systems, including orchestration layers, tool-use definitions, and human-in-the-loop guardrails.
- Scalability: Ensure all solutions are built using CodeRoad’s preferred technology stacks and reference architectures to maximize cross-client reuse.
- Build vs. Buy Governance: Evaluate when to leverage third-party AI platforms versus when to build proprietary agentic components that contribute to CodeRoad’s long-term enterprise value.
- Execution Oversight: Act as the technical "North Star" for our nearshore engineering teams, ensuring the delivered product matches the architectural intent and client business outcome.
- IP Identification: Proactively identify patterns in client implementations that can be "graduated" into repeatable products or platform features for Engine 3.
Qualifications & "Engine-Fit"
- Technical Depth: Hands-on experience with LLM orchestration frameworks (e.g., LangChain, CrewAI, AutoGen) and modern cloud-native architectures.
- Business Fluency: Ability to discuss ROI, margin impact, and operational risk with C-suite stakeholders and private equity sponsors.
- Consultative Presence: Experience working within or alongside boutique consulting firms to deliver high-touch professional services.
- Pragmatic Discipline: A "Value-First" mindset that avoids hype-driven AI experimentation in favor of solutions that improve economics and delivery quality.
Success Looks Like…
- Repeatability: A reduction in "time-to-first-pilot" for new clients through the use of standardized AI frameworks.
- Account Growth: High client trust leading to the graduation of "Turnkey Solutions" (Engine 2) into "SaaS/Platform" engagements (Engine 3).
- Delivery Excellence: Implementation of agentic solutions that improve client economics without introducing unmanaged technical risk.
Requirements
- Must be legally authorized to work in the United States (no sponsorship available).
- Must be available to travel within the United States as required for customer deployments.
Compensation & Benefits
CodeRoad offers a comprehensive and competitive benefits package, including medical, dental, and vision insurance, retirement plan, and paid time off (PTO).
The salary range for this role is $140,000–$250,000 per year.
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