Marketing AI agent Builder
Role Overview:
As our Marketing AI Agent Builder, you will be the lead architect for our "agentic"
marketing stack. Your goal is to move beyond simple automation (if-this-then-that)
toward autonomous systems that reason through marketing data, execute
multi-channel campaigns, and self-correct based on performance. This is a "Builder"
role part Engineer, part Strategist, part Data Scientist.
This is a remote role with the option to work anywhere in NA.
Core Responsibilities
Intelligent Research & Segmentation: Deploy agents to crawl the web for intent
signals (hiring changes, funding, news) to dynamically update ICP segments and
enrich CRM records in real-time.
Autonomous Campaign Management: Build agents that independently monitor
live campaigns (Search, Social, Email) and autonomously reallocate budgets or
pause underperforming creatives based on real-time ROI.
Dynamic Lead Nurturing: Design agents that use Natural Language Processing
(NLP) to "read" prospect behavior and trigger personalized, multi-step nurture
sequences without manual intervention.
Performance & Guardrails: Establish "human-in-the-loop" protocols and
evaluation frameworks to ensure agent outputs align with brand voice and
security standards.
System Orchestration: Connect AI agents to our core stack including
HubSpot/Salesforce, 6sense, and Google Analytics ensuring seamless data
flow and automated write-backs to the CRM.
Qualifications & Skills
Experience: 2 4 years in Growth Engineering, ideally with experience scaling a
mid-market SaaS revenue engine.
AI Tooling: Proficiency with agent orchestration frameworks (e.g., LangGraph,
CrewAI) or low-code builder platforms (e.g., Claude CoWork, CodeX)
Agent Orchestration: Experience with low-code/no-code platforms (e.g., Clay,
Zapier Central, Make.com) or code-based frameworks (e.g., LangGraph, CrewAI).
Prompt Engineering: Ability to design complex "reasoning loops" that prevent
hallucinations and ensure professional, brand-aligned output.
Data Savvy: Comfortable working with JSON, APIs, and RAG
(Retrieval-Augmented Generation) to feed agents the right context from your
company s internal knowledge base.
Marketing Expertise: Knowledge of B2B buyer journeys, attribution models, and
demand generation tactics.
Sales AI Agent Builder
Role Overview:
You will architect and manage a fleet of autonomous Sales Agents that perform
end-to-end prospecting, qualification, and meeting scheduling. Unlike traditional Sales
Ops, you won't just build workflows; you will build reasoning systems that research
prospects, handle objections, and manage their own "inboxes" to deliver qualified
meetings to our SEs. This is a remote role with the option to work anywhere in NA.
Key Responsibilities
Autonomous Lead Qualification: Design agents to "vet" inbound leads by
querying external data sources and internal CRM history to determine if they
meet our Ideal Customer Profile (ICP).
Inbox Management & Objection Handling: Deploy agents (using LLMs like
GPT-4o or Claude) that can read incoming emails, categorize intent, and
draft/send context-aware replies to handle common objections.
Live Sales Assistant (RAG): Build a "Sales Knowledge Base" using
Retrieval-Augmented Generation (RAG) so agents can instantly reference case
studies, pricing, and competitor battlecards during autonomous chats.
CRM Data Integrity: Ensure agents "write back" all interactions to
Salesforce/HubSpot, keeping data clean and attribution accurate without rep
intervention.
Qualifications
Experience: 4+ years in Growth or Solutions Engineering in a B2B SaaS
environment.
AI Tooling: Experience with "Agent-as-a-Service" platforms (e.g., 11x, Regie.ai,
Lyzr) or building custom agents via LangChain / LangGraph.
Sales Stack Mastery: Deep expertise in Salesforce/HubSpot, Salesloft/Outreach,
and data providers like ZoomInfo or 6sense.
Analytical Rigor: Ability to A/B test agent prompts and "reasoning loops" to
improve meeting-set rates
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