Outbound AI Engineer, Data

Nimble is hiring an Outbound AI Engineer to support our Enterprise sales motion focused on Data and Retail / CPG accounts.

This is not a traditional BDR role.

The role supports a focused Enterprise pod and is accountable for helping that pod create a Sales Working pipeline and ARR. The AI Outbound Engineer owns the work traditionally associated with top-of-funnel, but the role does not stop at booking meetings. They are expected to use AI agents, automation, account research, GTM assets, and follow-up support to help the pod open doors, progress opportunities, and generate revenue.

This person will focus on companies that need live web data to support their core business operations. That includes Retail and CPG companies, but also other businesses that rely on external web data for pricing, product intelligence, market monitoring, competitive intelligence, location data, listings, reviews, content, or other business-critical workflows.

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
• Build repeatable account research workflows for target accounts and verticals
• Build lightweight tools, workflows, dashboards, and automations that help the pod prioritize accounts and execute faster
• Create 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

This role is not about occasionally using ChatGPT or Claude to write outbound emails.

We are looking for someone who can use AI agents, workflows, automation, and agentic loops to make the outbound motion faster, sharper, and more scalable across a focused set of target accounts.

The right person should be comfortable using AI as a research, workflow, automation, and GTM execution layer.

That means using LLMs where useful, but also connecting them to tools, data sources, workflows, and repeatable processes that help the pod operate more effectively.

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
• Build account briefs that summarize company priorities, business model, data needs, public web presence, competitive landscape, and relevant business initiatives
• Identify relevant stakeholders and buying committees across data, analytics, ecommerce, operations, pricing, product, strategy, and revenue teams
• Turn account research into relevant outbound angles by persona, account, and use case
• Build repeatable messaging frameworks for different verticals, segments, and buyer types
• Create personalized outreach based on account-specific signals, not generic AI-written copy
• Use AI agents to analyze websites, product catalogs, marketplaces, pricing pages, job postings, news, earnings calls, reviews, listings, and other public web signals
• Build lightweight workflows, automations, dashboards, and internal tools that help the pod prioritize accounts and execute faster
• 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