AI Architect - Generative AI & Enterprise Solutions

• Drive the end-to-end architecture and technical vision for generative AI within the function - reference architectures, patterns, and standards that teams build against.
• Make authoritative technology decisions, selecting the right models, frameworks, and agent harnesses for each use case, balancing capability, latency, cost, and risk.
• Move solutions from proof-of-concept to production with realistic, production-grade designs - covering orchestration, retrieval (RAG), evaluation, observability, guardrails, and human-in-the-loop.
• Integrate GenAI into the existing cloud solutions and automation platform (AWS, CI/CD toolchain, ITSM) so GenAI is a first-class, governed capability.

Running AI at Scale

• Design for scale and operational excellence for GenAI workloads - throughput, latency, reliability, and cost optimization (token economics, caching, model routing).
• Establish the operational foundation including evaluation pipelines, monitoring, drift/quality management, and incident response for Agentic solutions.
• Bake in guardrails such as security, data privacy, responsible-AI, hallucination mitigation, and regulatory compliance into every architecture.

Executive Engagement & Strategy

• Advise and influence to CXO-level leaders, translating complex AI concepts into clear business value, trade-offs, risks, and roadmaps.
• Shape the generative-AI strategy and roadmap for the enterprise, aligning technology investment with business outcomes and priorities.
• Build and present business cases, ROI, and build-vs-buy analyses for AI initiatives.
• Serve as an evangelist and trusted expert - to executives, engineering teams, and external partners - and champion an enterprise AI vision.

Enablement & Governance

• Mentor and upskill engineering teams and set architecture governance, review gates, and reusable building blocks.
• Define and steward AI governance, standards, and best practices in partnership with security, data, and legal.

• Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field - or equivalent practical experience.
• 10+ years of experience in software/AI engineering and architecture, including senior technical leadership on large-scale systems.
• Recognized depth in generative AI: LLMs, prompt/context engineering, RAG, agent frameworks (e.g., LangChain, Amazon Bedrock Agents), and agent harnesses.
• Proven track record designing and running GenAI solutions in production at scale - including evaluation, observability, cost, and reliability.
• Deep hands-on knowledge of AWS and its AI services (e.g., Amazon Bedrock), plus core cloud infrastructure (compute, networking, IAM, containers).
• Strong grounding with enterprise architecture practices, integration, and the modern DevOps toolchain (GitHub, Jenkins, Artifactory, SonarQube).
• Exceptional communication and executive-presence skills - able to hold credible, persuasive CXO-level conversations and articulate complex technology in business terms.
• Solid understanding of responsible-AI, security, and data-governance considerations for enterprise AI.

3.73.7 out of 5 stars United States Hybrid work $150,000 - $170,000 a year - Full-time

This is a senior, highly visible role that blends deep technical mastery with executive influence. You are expected to be a recognized expert in generative AI - frameworks, agent harnesses, and the realities of production deployment - and equally comfortable in the boardroom, translating complex technology into clear business value for CXO-level stakeholders and helping shape enterprise AI strategy.