AI Architect: Generative & Agentic Solutions Leader

International Business Machines Corporation

Boston (MA)

Hybrid

USD 170,000 - 210,000

Full time

3 days ago

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Job summary

IBM Consulting is seeking an AI Architect to lead enterprise agentic AI initiatives across Google Gemini, Vertex AI, SAP, Salesforce, and Databricks. You will drive scalable, governed AI solutions while coordinating across client teams and engineering colleagues in a hybrid delivery model.

The role combines hands-on architecture leadership with governance, tooling orchestration, and cross-platform integration, requiring senior technical depth and strong collaboration across enterprise teams.

Qualifications

Strong hands-on experience with Google Cloud Platform AI services including Vertex AI, Gemini API, Agent Builder, AI Studio, and related GCP AI capabilities.
Experience designing and implementing agentic AI systems including multi-agent coordination, tool-calling patterns, planning workflows, memory/state management, and autonomous orchestration.
Experience integrating enterprise AI ecosystems across SAP AI (BTP/Joule), Salesforce Einstein and Databricks.

Responsibilities

Design and architect enterprise agentic AI solutions using Google Gemini, Vertex AI, Agent Builder, and IBM Enterprise Advantage platform services.
Define multi-agent and agent-to-agent orchestration patterns across SAP AI (BTP/Joule), Salesforce Einstein, Databricks, and enterprise systems.
Lead architecture and implementation of long-running AI workflows including task coordination, state management, memory handling, tool use orchestration, and workflow resiliency.
Build enterprise AI integration patterns leveraging APIs, event-driven architecture, microservices, and cloud-native services on GCP.
Develop Retrieval-Augmented Generation (RAG) and enterprise knowledge solutions using Databricks data products and enterprise data platforms.
Implement AI governance, guardrails, safety filters, access controls, auditability, and compliance mechanisms aligned to regulated utility industry requirements.
Define AI solution standards, reusable architecture patterns, observability controls, and operational governance for production AI systems.
Collaborate with client stakeholders, business teams, AI engineers, platform teams, and enterprise architects to align AI architectures with business objectives.
Provide technical leadership and architecture governance for the Romania-based AI engineering team, including design reviews, implementation guidance, and engineering standards.
Support AI solution estimation, roadmap definition, technical risk management, and production readiness reviews.