Enterprise AI Architect

We are looking for an “Enterprise AI Architect". Please see the job details below: Job Title: Enterprise AI Architect Client Location: San Jose, CA – Hybrid (2-3 days) Remote/ Onsite/ Hybrid: Hybrid Job Description Summary We are looking for an experienced Enterprise AI Architect to assess enterprise RTB operations and design AI-first, predictive, and autonomous managed services solutions. The role will work closely with US-based business and IT stakeholders and coordinate with offshore AI teams. Key Responsibilities Identify high-value AI/Agentic opportunities across L2C, S2P, Finance, and RTB operations. Lead consultative discovery sessions with product, project, and leadership teams to evaluate existing tool ecosystems and connect technical AI solutions with meaningful business use cases and ROI. Analyze ServiceNow/Jira incidents, SOPs, and operational processes to identify automation opportunities. Design AI agents, multi-agent workflows, RAG solutions, and self-healing automation. Architect AI solutions across Oracle Fusion, Salesforce, Zuora, MuleSoft/OIC, and AWS. Establish Human-in-the-Loop controls, security guardrails, and AI governance. Ensure compliance with SOX, ITGC, SoD, PII, and data privacy requirements. Lead onsite AI workshops, POCs, and innovation initiatives with senior stakeholders. Define AI performance metrics, ROI, operational efficiency, and cost optimization. Required Skills & Qualifications Technical Depth & Architectural Leadership (70-80%): 8+ years of Enterprise Architecture experience with 3+ years in AI/ML, GenAI, or Intelligent Automation. Strong hands-on experience with Agentic AI / LLM frameworks such as LangChain, LangGraph, CrewAI, or AutoGen, plus modern AI stacks and agentic orchestration (e.g., Salesforce Agentforce, Oracle Agent Studio, Snowflake). Strong knowledge of LLMs, prompt engineering, RAG, and AI agent architecture. Experience with at least two enterprise platforms: Oracle Fusion, Salesforce, Zuora, or RevPro. Strong understanding of REST/SOAP APIs, MuleSoft, OIC, AWS, and OAuth. Experience with AI governance, security, observability, and enterprise integration. SaaS Business Process Acumen (20-30%): Foundational familiarity with high-tech SaaS business models and quote-to-cash (Q2C) operations—specifically covering source-to-pay, order processing, renewal motions, and complex amendment lifecycles (upsell, down-sell, cross-sell). Consultative Mindset & Communication: Excellent stakeholder management and communication skills with the ability to work directly with US business and IT leadership to build consensus and drive AI adoption. Good to Have Experience with Datadog/APM and AI-Ops monitoring. ITIL, DevOps, SOX, or enterprise governance experience. Experience delivering AI POCs and driving enterprise AI adoption.1 Prior onsite consulting experience in the US Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries of the position across all US locations. Within the range, individual pay is determined by work location and additional job-related factors, including knowledge, skills, experience, tenure and relevant education or training. The pay scale is subject to change depending on business needs. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Additional compensation may include benefits, discretionary bonuses, and equity Show more Show less