Applied AI Engineer

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.