Job Description
Job Description
Location: Major U.S. tech hub (on-site or flexible setup)
Work Model: Full-time, startup environment
Minimum Experience: Strong production engineering experience; startup or 0→1 systems preferred
Role Summary
Our client is a fast-growing, venture-backed AI startup building agentic recruiting technology that replaces traditional outbound recruiting workflows with end-to-end autonomous systems. The platform focuses on sourcing, engaging, qualifying, and matching passive candidates directly with companies—without job boards or traditional applications.
The company has achieved rapid early traction, growing from launch to over $1M in ARR within six months and sustaining approximately 40% month-over-month growth. They are now scaling core infrastructure to support significant expansion.
This role is a hands-on engineering position with high ownership, direct collaboration with technical leadership, and frequent production deployments. The successful candidate will design and build foundational systems that power large-scale, AI-driven recruiting workflows.
The Opportunity
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Work on infrastructure that directly replaces manual recruiting workflows at scale
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Build systems used by real customers immediately after release
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Join at an early stage with meaningful influence on architecture, product direction, and technical standards
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Contribute to scaling a proven product by 100x
Key Ownership Areas
The engineer will own one or more of the following systems:
Autonomous Outreach Infrastructure
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Build scalable systems for high-volume email and SMS outreach (100K+ candidates)
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Ensure personalization, deliverability, response handling, and compliance at scale
Candidate Intelligence & Data Pipeline
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Design parsing, normalization, and enrichment pipelines across diverse data sources
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Use LLMs to extract skills, infer seniority, and convert unstructured data into searchable, structured profiles
Agentic Conversation Systems
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Architect AI-driven conversational flows that qualify candidates, answer questions, coach interview preparation, and manage scheduling
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Balance automation with human-like interaction quality
Real-Time Matching & Ranking Engine
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Build low-latency search and ranking systems focused on skill alignment, trajectory, and fit—not keyword matching
Technology Stack
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TypeScript, React, Next.js
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Supabase, Prisma
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Typesense or similar search infrastructure
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LLM APIs (e.g., OpenAI- or Anthropic-compatible models)
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Workflow orchestration tools
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Modern developer tooling and AI-assisted coding environments
Required Background & Attributes
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Proven experience shipping production systems that operate at meaningful scale (users, data, or complexity)
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Comfort working across the full stack—from frontend components to database performance issues
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Hands-on experience using LLMs beyond simple prompting (e.g., embeddings, retrieval-augmented generation, agent frameworks)
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Strong product judgment and ability to make decisions with incomplete information
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Bias toward action: ship, measure, iterate
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Experience owning and delivering a system end-to-end (startup, side project, or internal platform)
Candidates who do not meet every requirement but demonstrate exceptional ownership or technical achievement are encouraged to apply.
Team & Working Style
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Small, senior founding team with prior startup and scale-up experience
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Direct collaboration with founders and technical leadership
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High-trust, high-ownership environment
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Fast-paced, execution-focused culture
Interview Process
Designed to be efficient and respectful of candidate time:
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Introductory conversation with a founder
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Technical deep dive focused on past systems and design thinking
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Short take-home exercise reflecting real-world work (2–4 hours)
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Final team conversation
Compensation & Benefits
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Competitive salary with significant equity participation
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Health insurance
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Learning and development budget
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Flexible work setup
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Visa sponsorship available
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High-impact role at an early-stage, high-growth AI company