Principal AI Architect driving AI solutions and enterprise architecture for a leading health tech company. Guiding scalable AI initiatives within B2B SaaS environments.
Responsibilities
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.
Experience with Salesforce ecosystem including Einstein, Agentforce, and Data Cloud is preferred.
Strong understanding of enterprise security architecture and data privacy principles.
Proven ability to translate business capabilities into scalable technical solutions.
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