Founding AI Engineer

Founding product engineer role — the first engineering hire who will define the technical and cultural foundation of the company. Delegate builds AI coworkers — not chatbots — that own entire business processes end-to-end for enterprise teams. They call it the Agentic Process Engine, starting with sales (post-call briefs, follow-ups, pipeline hygiene, win wires, deal risk detection) and expanding into other operational functions.

~50/50 split between core agent infrastructure and end-user-facing product. Trajectory: writing code alongside founders today → leading a team and owning critical product surfaces in 2 years. Long-term vision: redefine work, where individuals manage agents performing most tasks.

Hard problems they're solving:

• Designing agent systems that replace human workflows (not just assist)
• Multi-step autonomous orchestration that holds state and adapts to context
• Engineering around hallucination, state drift, over-triggering, and trust collapse at scale

• Build the core Agentic Process Engine — the system that runs business units, not individual tasks
• Build the sales agent layer: post-call briefs, follow-ups, pipeline hygiene, win wires, proactive deal risk detection — all autonomous
• Full stack: frontend, backend, orchestration infrastructure
• Architecture for agent coordination across integrations, long-term memory, and reliable action-taking
• Build the foundation of an engineering team they'll eventually hire and lead
• Work with founders to shape product definition, interface with customers to identify pain points, and build repeatable solutions
• Several design partnerships are materialising and require engineering support — this hire directly unblocks those

Must-have:

• 1–7 years of full-stack engineering experience (recently expanded from 3+ YOE to open up top of funnel)
• Shipped real AI agent systems — tool use, multi-step reasoning, memory, autonomy (not just RAG/chatbots)
• Early-stage startup experience — high ambiguity, no spec, no PM, made something out of nothing
• Full-stack proficiency — team uses Python and React
• Basic distributed systems knowledge (e.g., Temporal — not Temporal-specific)
• General LLM understanding
• Opinionated — strong views on system design, willing to push back
• High agency, strong follow-through, output-driven
• Undergrad in CS (top 100 school for new grads)
• Based in SF or willing to relocate

Strongly preferred:

• VC-backed, seed–Series B AI startup experience
• Prior founder or founding engineer experience, OR rapid promotion track record
• Replaced (not augmented) a business process with AI end-to-end
• Deep integrations with GTM tools: Salesforce, Gong, Outreach, Slack, Google Workspace
• Workflow orchestration or event-driven systems at scale
• Thoughtful on human-in-the-loop design (when agents act vs. escalate vs. stop)
• Strong network of engineers they'd bring along

Target companies: Perplexity AI, Scale AI, Cognition, Applied Compute, Google DeepMind, Notion, Vercel, Retool, Figma, Linear (plus 9 more)

Disqualifiers:

• Pure frontend or pure backend (must be full-stack)
• Large, slow-moving enterprise backgrounds (e.g., JP Morgan, SAP)
• Managers without recent hands-on coding
• Contract or short-term roles only — needs full-time startup experience
• Candidates who can only articulate breadth, not depth — must show end-to-end system design in agent systems

1. Founder interview — behavioural
2. Founder interview — technical
3. One-day paid work trial

• First engineering hire — defines architecture, culture, and category
• Founders with proven enterprise scale — Scale AI $0→$100M in ~2-3 years
• Tier-1 backing — Felicis-led, $8M seed, marquee unicorn design partners
• Genuinely unsolved problem — agentic process automation, not chatbots
• Founding equity — 0.5–5% with flexibility on base/equity mix (preference for higher equity + competitive base)
• Competitive base — $230K–$300K
• Direct founder access — every customer call, every product decision
• Output over hours culture — not 996, but open discussions, rapid evolution, quick pivots, strong decision-making