Business Development Rep - US

Overview

You're prospecting into enterprise companies to book meetings for AEs to demo Ona's AI software engineering agents. This is a technical sale - you're reaching out to VPs of Engineering, CTOs, and engineering platform teams about using AI agents to handle code migrations, CVE fixes, and code reviews. It's category creation, so most prospects don't know what "AI software engineers" means yet.

Role Snapshot

Company Context

Stage: Likely Seed/Series A (79 employees, actively hiring early GTM)

Size: 79 employees

Growth: Small enough that you'll work directly with founders (Eva, Lydia, Karthik mentioned). Early GTM build-out phase.

Market Position: Category creator - "AI software engineers" is a new concept. You're educating the market, not competing on features yet.

GTM Reality

Pipeline Sources:

• 90%+ Outbound - You're building the pipeline from scratch via targeted ABM campaigns
• <10% Inbound - Some website traffic and demo requests, but limited brand awareness at this stage
• Minimal Partners/Referrals - too early for a mature channel program

SDR/AE Structure: BDR books, AE closes. Small team so expect to work closely with just 1-2 AEs.

SE Support: Likely some technical support post-meeting, but you need to understand the product well enough to have technical discovery conversations.

Competitive Landscape

Main Competitors: GitHub Copilot (different use case but budget competitor), internal engineering automation tools, other AI coding startups emerging

How They Differentiate: Focus on autonomous agents that run in the background vs. co-pilots that assist developers. Enterprise-grade security/governance layer.

Common Objections:

• "We're already using Copilot"
• "Our engineers won't trust AI to write production code"
• "Security concerns with AI accessing our codebase"
• "Too early/not ready to adopt AI agents"

Win Themes: Scale engineering output without hiring, handle boring/repetitive tasks (migrations, CVE fixes), enterprise compliance built-in

What You'll Actually Do

Time Breakdown

Account Research (25%) | Outbound Activities (50%) | Meeting Prep/Handoffs (15%) | Internal (10%)

Key Activities

• Account Research: Spend 1-2 hours daily researching target companies - looking at their tech stack, recent engineering blog posts, GitHub repos, job postings to understand their engineering challenges. Building persona maps of who to target.
• Cold Calling: Make 40-60 calls per day to engineering leaders. Most go to voicemail. You're trying to get past gatekeepers to reach VPs of Engineering or Engineering Platform teams. Expect low connect rates (5-10%).
• Email Sequences: Write personalized email sequences (5-7 touches) for each account in your ABM list. You'll reference specific technical challenges you found in research. A/B test subject lines and messaging constantly.
• LinkedIn Outreach: Send connection requests and InMails to engineering leaders. Try to build rapport before the hard pitch. Most won't respond, but you're building familiarity.
• Discovery Calls: When someone agrees to a 15-min call, you qualify them - size of engineering team, current automation efforts, pain points with code quality/velocity, budget authority. About 50% of these convert to qualified meetings.
• Meeting Handoffs: Prep AEs on accounts before meetings - share all your research notes, what resonated in discovery, key stakeholders identified.

The Honest Reality

What's Hard

• Category Education: You can't just pitch features - you have to explain what "AI software engineers" means first. Many calls end with "interesting, but we're not ready" because it's too early/novel.
• Low Response Rates: Engineering leaders are bombarded with AI tool pitches. Your connect rate on cold calls will be 5-10%. Email response rates around 2-3%. You'll hear a lot of silence.
• Technical Credibility: You need to understand concepts like CI/CD, code review processes, CVE remediation, and technical debt well enough to have credible conversations with senior engineers. If you can't speak their language, you get dismissed quickly.
• Long Sales Cycles After Handoff: Even when you book a meeting, deals take 6-9+ months to close (enterprise security reviews, POCs, buy-in from multiple teams). You won't see immediate revenue results from your work.
• Repetitive Grind: Most of your day is research → personalize → send → follow up → repeat. It's methodical, repetitive work. You'll send 100+ emails to get 2-3 replies.

What Success Looks Like

• 15-20 qualified meetings booked per month that AEs accept (meet ICP criteria, have budget/authority, have a real use case)
• 40%+ meeting show rate - prospects you book actually show up and are engaged
• High conversion from your meetings to opportunities - AEs move 50%+ of your meetings into active pipeline
• Pipeline contribution - The meetings you book turn into real deals over time (though you won't see this for 6-12 months)

Who You're Selling To

Primary Buyers:

• VP of Engineering / Head of Engineering (teams of 100-500+ engineers)
• Director of Engineering Platform / Infrastructure
• CTO (at smaller enterprises, 200-1000 employees)

What They Care About:

• Engineering velocity - Can they ship faster without hiring more engineers?
• Technical debt - Backlog of migrations, CVE fixes, code quality improvements they can't prioritize
• Security/Compliance - Can AI agents access their code securely? What's the governance model?
• Developer experience - Will their engineers actually use this or resist it?
• ROI - What's the cost vs. hiring more engineers or continuing to do this work manually?

Requirements

• Technical curiosity - You need to learn how software engineering teams work, even if you're not an engineer yourself. Read engineering blogs, understand developer workflows.
• Persistence - You'll get ignored 95% of the time. You need to keep iterating messaging and not take rejection personally.
• Strong writing skills - Your emails need to be crisp, technical enough to be credible, and personalized enough to stand out from 50 other AI tool pitches they're getting.
• ABM mindset - This isn't about volume. You're going deep on 50-100 accounts, not blasting 1000s of leads.
• Comfort with ambiguity - Early-stage company, new category. Messaging and positioning will evolve based on what you learn in conversations. There's no playbook yet.
• 1-2 years BDR experience preferred - They want someone who knows outbound mechanics but can adapt to a technical, category-creation sale.