Head of AI

Job description

## Role Overview We are seeking a visionary and execution-focused **Head of AI (Agentic Outreach)** to spearhead the evolution of our growth, sales, and engagement marketing engines. In this role, you will design, build, and scale an ecosystem of autonomous AI agents capable of hyper-personalized, context-aware, and multi-channel outreach. You will bridge the gap between advanced machine learning engineering and strategic business growth, moving beyond simple template automation to build dynamic, self-learning agentic workflows that orchestrate complex B2B/B2C communication strategies. ## Key Responsibilities ### 1. Strategy & Architecture - **Vision & Roadmap:** Define the strategic roadmap for agentic outreach, transitioning from static sequence automation to autonomous, goal-driven AI agent networks. - **System Architecture:** Design and oversee the infrastructure for multi-agent systems that handle lead sourcing, intent signaling, content generation, and multi-turn conversational follow-ups. - **Guardrails & Ethics:** Establish strict compliance, data privacy (GDPR/CCPA), brand voice alignment, and safety guardrails to ensure AI agents interact ethically and accurately. ### 2. Technical Execution & AI Engineering - **Agent Orchestration:** Build and optimize workflows using framework stacks like LangChain, CrewAI, AutoGen, or custom-built internal orchestration layers. - **RAG & Memory Systems:** Implement advanced Retrieval-Augmented Generation (RAG) and persistent memory vector databases so agents maintain deep context across long-term buyer journeys. - **Model Optimization:** Fine-tune, prompt-engineer, and select the optimal mix of proprietary (OpenAI, Anthropic) and open-source (Llama, Mistral) LLMs to balance cost, latency, and performance. ### 3. GTM Integration & Analytics - **Data Pipeline Integration:** Connect agentic workflows seamlessly with our modern data stack, CRM (Salesforce/HubSpot), sales engagement tools, and data enrichment APIs (e.g., Clay, Apollo, ZoomInfo). - **Loop Optimization:** Build reinforcement learning loops based on positive/negative conversion signals (e.g., booking a demo vs. "unsubscribe" requests) to continuously improve agent persuasion and timing. - **KPI Tracking:** Own the performance metrics of AI-driven outreach, including pipeline generated, response quality scores, deliverability rates, and ROI. ## Qualifications & Skills ### Technical Requirements - **AI/ML Expertise:** 5+ years and above of experience working with Large Language Models (LLMs), prompt engineering, and embeddings. - **Agentic Frameworks:** Proven hands-on experience building autonomous agent architectures, multi-agent frameworks, and tool-use (function calling) loops. - **Programming Proficiency:** Expert-level Python developer with experience in AI libraries and vector databases (Pinecone, Milvus, Qdrant, etc.). - **Data & API Integration:** Deep understanding of web scraping, reverse APIs, webhook orchestration, and complex data enrichment pipelines. ### Leadership & Strategic Skills - **Growth Mindset:** Strong understanding of modern outbound B2B marketing, sales development (SDR/BDR) playbooks, and growth hacking principles. - **Team Building:** Experience leading and mentoring cross-functional teams of AI engineers, data scientists, and growth marketers. - **Analytical Rigor:** Strong statistical background to design and evaluate rigorous A/B testing frameworks for agentic variations. ## Preferred Experience - Experience in a fast-paced B2B SaaS environment or a high-growth tech startup. - A portfolio of shipped AI products, open-source contributions to agentic frameworks, or public writing/research on the future of autonomous systems. - Familiarity with sophisticated email deliverability infrastructure (domain warming, spintax, rotating IPs).