Responsibilities

Design and ship multi-step, production-grade AI agents that automate complex GTM workflows end-to-end
Translate business requirements into robust agent architectures, including state management, tool use, orchestration, and guardrails
Build multi-agent systems where specialized agents collaborate, hand off work, and maintain context across workflow stages
Integrate agents with Salesforce APIs (read/write), mapping object models (Leads, Contacts, Opportunities, custom objects) and handling authentication securely
Connect agents to structured business data in Snowflake and reason over it reliably at runtime
Partner with IT/Security and Data Engineering to align on infrastructure, access controls, and production readiness
Define and improve reliability patterns: error handling, fallback behaviors, output validation, monitoring, and post-launch iteration
Deliver in an agile cadence with proper review gates across dev → staging → QA → production

Requirements

Production agentic systems experience: Shipped at least one multi-step AI agent to production that real users rely on daily
Multi-agent orchestration: Hands-on experience building systems where multiple agents collaborate (e.g., LangGraph, CrewAI, AutoGen, or equivalent patterns)
CRM + business systems integration: Deep comfort integrating with Salesforce via APIs, including auth, object models, and real-world GTM workflows
LLM API proficiency: Strong hands-on experience with Anthropic Claude, OpenAI, or equivalent — tool use/function calling, context management, and reliable parsing in production
GTM domain knowledge: Working understanding of how Sales, CS, Marketing, and RevOps operate (deal cycles, renewals, pipeline, customer health, partner workflows, revenue reporting)
Security-aware architecture: Ability to design for RBAC, data isolation, and auditability; familiarity with auth patterns like OAuth/JWT/SSO
Python (production quality): Strong Python with async patterns, logging/observability, error handling, and deployment considerations
Workflow automation + API integration: Experience building reliable integrations across external systems
Data warehouse connectivity: Experience building agents that query Snowflake (or equivalent) and reason over structured data safely and consistently
Requirements translation: Think in systems and workflows, push back on weak requirements, and propose better approaches grounded in production reality

Experience building lightweight interface layers (React, Next.js, or similar) on top of agent backends
RAG architecture experience (vector databases, chunking strategies, embedding pipelines)
Experience replacing SaaS tools with purpose-built AI workflows (build vs. buy judgment)