Outbound AI Engineer

As an Outbound AI Engineer at Nimble, you’ll support a focused Enterprise pod and help that pod create pipeline and ARR. You’ll own the work traditionally associated with top-of-funnel, but your role will not stop at booking meetings.

You’ll use AI agents, automation, account research, GTM assets, and follow-up support to help the pod open doors, progress opportunities, and generate revenue.

The goal is simple: help the pod create more pipeline and ARR from the accounts we care about.

You do not need to be a software engineer.

You do need to be resourceful, AI-native, and comfortable using modern AI tools to replace manual BDR work with better research, stronger personalization, faster execution, and more useful sales support.

Being good at prompting is helpful, but it is not enough.

We’re looking for someone who understands how to connect AI into actual GTM workflows and can think in terms of agents, workflows, tools, and repeatable systems.

What Makes This Role Different

Most BDR roles are built around activity volume.

This role is built around pod outcomes.

You’ll be expected to open doors and book meetings, but also to help the pod create better account strategies, better messaging, better assets, better follow-up, and better ways to engage the accounts we care about.

You are not just passing meetings to AEs and moving on.

You are part of the Enterprise pod and share the goal of creating pipeline and ARR from the accounts assigned to that pod.

The role combines the accountability of outbound with the leverage of AI, agents, automation, and GTM tooling.

Responsibilities:

• Support a pod of 2–3 Enterprise AEs
• Research accounts, stakeholders, buying committees, market signals, and relevant business initiatives
• Build AI-executed 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 assigned accounts and segments
• Build lightweight tools, workflows, dashboards, and automations that help the pod prioritize accounts and execute faster
• Create account-specific or segment-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

How We Expect AI to Be Used

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

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

You 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 you might use AI in this role:

• Build repeatable account research agents for assigned accounts and segments
• Create agentic workflows that gather, summarize, and structure public web signals across accounts
• Build account briefs that summarize company priorities, business model, public web presence, competitive landscape, and relevant business initiatives
• Identify relevant stakeholders and buying committees across target accounts
• Turn account research into relevant outbound angles by persona, account, and use case
• Build repeatable messaging frameworks for different segments, buyer types, and use cases
• Create personalized outreach based on account-specific signals, not generic AI-written copy
• Use AI agents to analyze websites, documentation, product pages, job postings, news, company updates, customer stories, technical content, 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…