Senior AI Architect for Business Systems

Responsibilities

• Architect and lead the technical execution of AI CoE initiatives, ensuring alignment with global business objectives.
• Design and implement GenAI solutions using AWS, Azure, Google Gemini and Google Cloud Platform (GCP) (model selection, prompt design, orchestration, governance).
• Build complex autonomous systems and multi-agent orchestrations leveraging n8n and the Model Context Protocol (MCP).
• Establish best practices for ModelOps, LLM security, data privacy, and ethical AI deployment across the enterprise.
• Integrate AI capabilities into Oracle platforms (Fusion, ERP, integrations) and Salesforce ecosystems (Sales, Service, Data Cloud, APIs).
• Define scalable architectures covering data ingestion, enrichment, model inference, security, and observability.
• Work directly with Trimble product, engineering, and business stakeholders to clarify requirements and outcomes.
• Drive AI solution delivery with minimal oversight, making architectural and design decisions independently.
• Collaborate with delivery teams using JIRA, Confluence, and Agile delivery practices.
• Ensure Responsible AI practices including explainability, data privacy, access control, and governance.
• Support POCs, pilots, and production rollouts, including performance optimization and cost management on GCP.
• Provide mentorship and technical guidance to data engineers and AI developers, fostering a culture of continuous learning and excellence in AI engineering.

Qualifications and Experience

• 8+ years of overall technology experience with 3–5+ years in AI/ML or GenAI architecture.
• Proven experience designing AI solutions on Google Gemini, Google Cloud Platform (GCP), and the overall Google ecosystem, including specific GCP services such as Vertex AI, BigQuery, Cloud Functions, APIs, IAM, logging, and monitoring.
• Deep experience with LLMs, GenAI workflows, and GenAI patterns involving RAG architectures, agents, embeddings, prompt engineering, fine tuning, vector stores, grounding, agent orchestration, and MLOps.
• Strong integration experience with Oracle (Fusion, ERP, databases, integrations) and Salesforce (Sales/Service Cloud, APIs, Data Cloud), including API‑driven integration patterns between AI services and enterprise platforms.
• Proven track record in RPA (UiPath, Automation Anywhere, or similar) integrated with AI.
• Strong background in API design, microservices, and modern cloud-native architectures.
• Experience with Oracle Fusion AI Studio, Oracle OCI, Salesforce Einstein, Agentforce, and Mulesoft is highly desirable.
• Pragmatism: The ability to choose the right solution over the coolest solution to meet a business deadline.
• Ability to work independently, make architectural decisions, and manage ambiguity.
• Competency in data pipelines and transformation for structured and unstructured data.
• Strong understanding of security, compliance, and governance in enterprise AI environments.
• Strong working knowledge of JIRA, Confluence, and Agile/Scrum methodologies.
• Ability to document architecture, decisions, and patterns clearly.
• Exceptional communication skills, with the ability to explain complex AI concepts to non-technical stakeholders and C‑suite executives.

Bonus Points

• Specialized experience with Oracle Fusion AI Studio, Oracle OCI, Salesforce Einstein, Agentforce, or Mulesoft.
• Background in multi-agent orchestration frameworks like n8n and Model Context Protocol (MCP).
• Experience combining Robotic Process Automation (RPA) tools with advanced generative AI.