Warning, we are looking for a real expert here. If you dabble in AI, or read a couple newsletters and are "faking it till you make it, you're not going to like working with us". We are a team of deep AI architects who are out to change the world. Our consulting company is getting busy and we need some more TRUE experts on board. We build "digital workforces" of AI agents for ocmpanies, spanning Sales (SDR), Product Management, Competitive Intel, and Legal,that work autonomously within a secure environment. We are not looking for simple "GPT wrappers." We need a robust, scalable architecture where agents share a unified Knowledge Graph, retain long-term memory, and execute complex business logic without hallucinating. Key Responsibilities Architect the Multi-Agent Framework: Design the orchestration layer (e.g., LangGraph, CrewAI, or AutoGen) that allows multiple agents to communicate and hand off tasks. Knowledge Infrastructure (RAG): Build a secure, private Retrieval-Augmented Generation pipeline that synthesizes data from CRM (Salesforce/HubSpot), support tickets (Zendesk), call recordings, and internal documentation. Agent Development: Sales/SDR Agent: Lead profiling, outbound prep, and automated CRM documentation. Competitive Intel Agent: Real-time market monitoring and win/loss analysis. Head of Product Agent: High-level synthesis of customer feedback into roadmap priorities. Technical & Success Agents: Internal and external support bots using historical case data. Security & Governance: Ensure all data is handled in a private, SOC2-compliant environment (Azure OpenAI, AWS Bedrock, or private VPC deployments). Required Skills Frameworks: Expertise in LangChain/LangGraph, CrewAI, or similar agentic orchestration tools. Vector Databases: Proficiency with Pinecone, Weaviate, or Milvus for high-dimensional data retrieval. LLM Engineering: Advanced prompt engineering, function calling, and structured output handling. Integrations: Experience with Zapier/Make.com or custom API integrations for CRM and Slack/Teams. Product Thinking: Ability to translate high-level business goals (e.g., "reduce churn") into specific agent behaviors. Preferred Qualifications Experience building "Human-in-the-Loop" systems for sensitive tasks (Legal/Pricing). Previous experience in SaaS or software company scaling. Ability to start with a Discovery/Architecture phase before moving to full implementation.