Job Summary
We are seeking an experienced Cloud Solutions Architect to architect and establish an enterprise agentic AI and data platform. The role will focus on designing reusable AI agents, enterprise applications, governance, security, observability, and human-in-the-loop controls. The ideal candidate will have extensive experience building and operating production-grade LLM and multi-agent systems, along with strong expertise in Snowflake, data engineering, cloud security, and enterprise architecture.

Key Responsibilities
Architect and establish reusable foundational agents that can be chained together to support complex data lifecycle tasks.
Design modular, task-specific AI agents and multi-agent orchestration frameworks.
Build and deploy user-facing agentic workflows tailored to enterprise requirements.
Design and implement enterprise-grade agent governance, security, and access controls.
Implement Single Sign-On (SSO), Role-Based Access Control (RBAC), and permission-scoped agent tool access.
Design and maintain an Agent Registry or centralized Agent Catalog.
Implement Model Context Protocol (MCP) and OpenAI-compatible interfaces and standards.
Integrate comprehensive observability, monitoring, logging, tracing, and guardrails for agentic systems.
Implement human-in-the-loop approval and review workflows for governed deployments.
Design and operate agent evaluation frameworks, including offline evaluation suites, regression testing, and measurable quality gates.
Monitor agent decisions, tool calls, token usage, costs, and production performance.
Troubleshoot agent failures, incidents, and production issues.
Design secure execution environments for agent-generated code, including sandboxed execution, automated validation, testing, and approval workflows.
Develop and maintain data solutions within the Snowflake ecosystem, including Snowpark, Streamlit, and Cortex AI.
Design and orchestrate modern ETL/ELT pipelines using DBT, SQL, and Python.
Establish scalable architecture patterns for data engineering and AI-enabled applications.
Implement audit logging, rollback procedures, and governance controls for production agentic systems.
Collaborate with data engineers, architects, business stakeholders, security teams, and other technical teams.
Provide technical leadership and architectural guidance across platform development initiatives.

Required Qualifications
10+ years of experience in software engineering, data engineering, cloud engineering, or related technical disciplines.
3+ years of experience building LLM-based systems.
2+ years of experience designing and operating production agentic AI systems serving live business users or workloads.
Proven experience leading the architecture of at least one multi-agent system that has operated in production for 12+ months.
Hands-on experience with supervisory, planner-worker, or similar multi-agent orchestration patterns.
Experience with tool calling, state management, memory management, and error recovery for long-running agentic workflows.
Production experience building and maintaining an Agent Registry or Agent Catalog.
Experience with agent-generated code execution, including sandboxed execution, automated validation, testing, and engineer review and approval workflows.
Experience building and operating production agent evaluation harnesses, including offline evaluation, regression testing, and quality gates.
Experience implementing production LLM observability, including agent tracing, tool-call monitoring, token usage, cost monitoring, and incident troubleshooting.
Experience implementing guardrails and human-in-the-loop controls, including approval gates, permission-scoped tool access, audit logging, and rollback procedures.
Production experience building or deploying MCP servers, MCP clients, or OpenAI-compatible tool interfaces.
Deep hands-on experience architecting solutions within the Snowflake ecosystem, including Snowpark, Streamlit, and Cortex AI.
Strong experience with agentic AI, LLMs, multi-agent orchestration, and AI platform architecture.
Strong Python and SQL skills.
Strong experience with DBT and modern ETL/ELT pipeline development.
Experience with CI/CD practices for data and AI platforms.
Strong understanding of enterprise security, IAM, SSO, SAML/OIDC, and RBAC.
Experience designing governance frameworks for public sector or highly regulated environments.
Excellent communication and collaboration skills.
Ability to work effectively with data engineers, architects, business stakeholders, and cross-functional technical teams.