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We are seeking a Principal AI Architect who will own both the AI strategy and enterprise architecture vision within a B2B SaaS and enterprise technology environment. This role is responsible for defining how AI and enterprise platforms evolve together, driving architectural decisions across product, revenue, and corporate systems. The ideal candidate will operate as a senior technical authority who shapes direction, challenges current-state thinking, and builds scalable architectures that support both customer-facing platforms and internal enterprise systems. This role combines deep hands-on AI architecture with strong enterprise platform experience and operates at the intersection of strategy, execution, and governance. This role has an approximate focus of 60% AI initiatives and 40% enterprise and solution architecture.
Job Responsibility:
Define and drive enterprise AI strategy and architecture within a B2B SaaS and enterprise technology environment
Design and govern AI solutions across the full customer lifecycle including marketing, sales, solution engineering, quoting, contracting, billing, revenue recognition, service, and customer success management
Architect and scale Generative AI, agent-based systems, RAG architectures, and intelligent automation in production SaaS platforms
Own enterprise architecture across core business and corporate platforms including customer, revenue, and operational systems such as CRM, quoting, contracting, billing, HR, and IT Service Management environments, with the ability to rapidly learn new technologies and design scalable solution architectures independent of specific tools or vendors
Architect and develop agentic enterprise capabilities that enhance business operations, workload orchestration, and user-facing automation
Design and implement LLM-powered agents using platforms such as Microsoft Copilot Studio and Salesforce Agentforce
Design orchestration patterns using frameworks and platforms such as Salesforce Agentforce, Microsoft Copilot, LangGraph, CrewAI, and LangChain to enable multi-agent collaboration across systems
Define architectural guardrails, platform standards, and lifecycle management practices for scalable, secure AI and enterprise systems
Act as a technical authority to review, challenge, and guide vendor, system integrator, and internal team architectures
Lead architecture governance by defining review frameworks, validating solution designs, and driving alignment to enterprise standards
Design target-state architectures, conduct gap assessments, and shape enterprise-wide solution roadmaps
Requirements:
12+ years of experience in enterprise, solution, or platform architecture roles within B2B SaaS or large-scale technology organizations
Proven experience designing and running AI systems in real production environments
Strong experience working across end-to-end B2B SaaS customer and revenue lifecycles including marketing, sales, quoting, contracting, billing, revenue recognition, service, and customer success platforms
Experience designing enterprise architecture for HR and corporate technology domains, with the ability to take ownership of these platforms and drive solution architecture without dependency on specific vendors or tools
Deep understanding of Generative AI, large language models, agent architectures, RAG patterns, and AI orchestration frameworks
Strong proficiency in Python with experience building backend services, APIs, and containerized workloads
Hands-on experience with LLM platforms such as OpenAI, Azure OpenAI, or Anthropic
Hands-on experience with agent frameworks such as LangChain, LangGraph, CrewAI, or AutoGen
Experience designing secure, scalable, multi-tenant enterprise and SaaS architectures
Experience leading architecture for large-scale business and technology transformation programs
Experience in Microsoft AI platforms like Azure foundry, Co-pilot agent is a must
Strong understanding of enterprise security architecture and data privacy principles
Proven ability to translate business capabilities into scalable technical solutions
Nice to have:
Experience with Salesforce ecosystem including Einstein, Agentforce, and Data Cloud is preferred