Outbound AI Engineer, Data + Retail / CPG
Responsibilities
- Support a pod of 2–3 Enterprise AEs focused on Data and Retail / CPG accounts
- Research accounts, stakeholders, buying committees, market signals, and relevant business initiatives
- Build and execute outbound campaigns across email, LinkedIn, phone, and other channels
- Book qualified meetings with target accounts
- Use AI agents, workflows, and automation to improve account research, personalization, messaging, sequencing, and follow-up
- Create repeatable account research workflows for target accounts and verticals
- Create lightweight tools, workflows, dashboards, and automations that help the pod prioritize accounts and execute faster
- Build account-specific or industry-specific GTM assets that help AEs open and progress conversations
- Support post-meeting follow-up, stakeholder mapping, and multi-threading
- Partner closely with AEs to help move opportunities from first meeting to pipeline and ARR
- Stay focused on assigned accounts and strategic GTM priorities rather than chasing easy meetings outside the target list
Requirements
- How We Expect AI to Be Used
- The right person should be comfortable using AI as a research, workflow, automation, and GTM execution layer
- Examples of how AI should be used in this role:
- Build repeatable account research agents for target accounts and verticals
- Create agentic workflows that gather, summarize, and structure public web signals across accounts
- Turn account research into relevant outbound angles by persona, account, and use case
- Create personalized outreach based on account-specific signals, not generic AI-written copy
- Build repeatable messaging frameworks for different verticals, segments, and buyer types
- Use AI agents to analyze websites, product catalogs, marketplaces, pricing pages, job postings, news, earnings calls, reviews, listings, and other public web signals
- Connect AI tools like Claude to external tools, data sources, workflows, and internal systems through Skills, APIs, automations, or similar approaches
- Use agentic loops to monitor accounts, surface changes, identify triggers, and suggest next actions
- Use AI to create GTM assets that help AEs open conversations and move opportunities forward
- Improve follow-up after meetings by summarizing context, identifying next stakeholders, creating tailored follow-up assets, and helping the AE multi-thread the account
- Continuously test and improve outbound messaging, targeting, and account strategy based on what is converting
About Us
Nimble is the real-time web search platform built for enterprise accuracy, completeness, and trust. We run Web Search Agents that actively navigate live websites using real browsers and reasoning, turning the public web into governed, decision-grade data for AI systems and high-stakes business use.
Unlike index-based “AI search” tools or brittle legacy scraping, Nimble makes the live web queryable on demand, delivering structured outputs that teams can verify and rely on. Our platform powers use cases where correctness matters: financial due diligence, real-time pricing and promotions, market intelligence, and AI systems that depend on fresh, complete data.
Trusted by leading enterprises like Home Depot, Uber, and Coca-Cola and backed by top-tier investors, Nimble sits at the intersection of AI, automation, and real-time web intelligence. As demand accelerates across AI, LLMs, and data-driven decisioning, we’re scaling quickly and looking for high-energy, driven teammates who thrive in fast-moving environments and want to help define a new category.
Why join Nimble?
- Work on a deeply technical platform powering real-time AI and enterprise decisions
- Help define the future of Web Search Agents and live web intelligence
- Build alongside a sharp, mission-driven team that moves fast, ships often, and takes ownership