The Company:
We are a high-growth, venture-backed startup rethinking the recruitment landscape through an AI-native marketplace. Having recently secured a significant seed round from top-tier investors, we have achieved strong product-market fit and are scaling rapidly to meet massive market demand.
Our business model leverages cross-sided network effects that compound as foundation models improve. We are currently a lean, high-output team looking for a "high-horsepower" engineer to help us increase capacity and navigate an expansive long-term roadmap.
The Role:
As one of the first engineers, you will own the applied AI systems that power our marketplace end-to-end. This is a builder-centric role focused on production-grade AI rather than theoretical research. You will partner directly with the founder and operations team to translate real-world feedback into scalable product features.
Role Composition:
- 60% Applied AI/ML: Model selection, prompting, fine-tuning, evaluation, and experimentation.
- 40% Full-Stack Implementation: Building APIs, backend services, data pipelines, and UI integrations.
Key Responsibilities:
Matching & Scoring Systems
- Refine candidate-job matching algorithms to improve placement quality and speed.
- Develop calibration tools that allow users to preview AI scoring logic.
- Implement systems to analyze previous rejections and surface promising new candidates.
- Build intelligent notification systems ranked by business value and fit.
Internal Automation & Operations
- Automate manual marketplace operations with intelligent workflows.
- Create AI-powered flagging for candidates or submissions requiring manual intervention.
- Develop feedback loops where the system learns from operational overrides to improve accuracy.
External-Facing AI Features
- Generate automated candidate summaries based on resumes, notes, and transcripts.
- Deploy retrieval-based assistants (RAG) to answer real-time questions about specific roles.
- Build suggestion engines and one-click submission features with pre-filled data.
Platform & Strategy
- Design evaluation protocols to measure model impact in production environments.
- Build internal infrastructure for offline evaluation and A/B testing.
- Stay current with emerging AI methods, making pragmatic decisions on which technologies to adopt.
- Collaborate on the long-term AI roadmap to balance rapid growth with technical durability.
Qualifications:
Required Experience
- 4+ years of software engineering experience, with a proven track record of shipping AI/LLM features in a production environment.
- End-to-end project ownership, from data pipeline design and model selection to deployment and iteration.
- Technical Proficiency: Deep experience with LLM APIs, embeddings, vector databases, and fine-tuning.
- Full-Stack Capability: Strong foundations in backend web development and API design.
Preferred Attributes:
- Experience in a founding team or an early-stage, high-growth startup.
- Background in HR-tech or recruitment marketplaces.
- Academic background from a top-tier technical institution (e.g., Stanford, MIT, CMU, Berkeley).
Compensation
The base pay range for this role is $170,000 – $230,000 per year.
