Full Stack Prototype Engineer

New York, NY, 10001

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Type: Contract

Reference ID: 32552991

Date Posted: 07/08/2026



Job Title: Full Stack Prototype Engineer
Location-Type: Remote OR Hybrid NYC- either OK (EST working hours)
Start Date Is: ASAP
Duration: (contract, perm, etc) 3 Month Contract (Can extend or potentially convert to FTE)
Compensation Range: 70-90$/hr W2
Benefits: Eligible for Health, Dental, Vision, 401K
Not eligible for Visa sponsorship

Job Description:

We're seeking a highly skilled and inventive Software Engineer to join the New A.I. Products & Platforms mission at one of our top clients. This pivotal team is dedicated to building and deploying the next generation of reader-facing, A.I.-driven experiences for one of the world's most reputable and trusted news organizations.

We are specifically looking for a "prototyper " — an engineer who possesses the ability to move with speed, build and ship tangible, high-quality products, and demonstrates a genuine, intuitive sense for what constitutes an excellent and engaging user experience. This role sits at the critical intersection of applied artificial intelligence and consumer product development. Your mission will be to transform emerging A.I. capabilities—including sophisticated language models, content embeddings, and semantic search techniques—into meaningful features that significantly enhance how readers Client, understand, and engage more deeply with our comprehensive and diverse content.

It is crucial that you thrive within an organizational context characterized by a strong culture of editorial judgment, independence, and trust. This context is fundamental and will heavily shape the definition of "good " and "responsible " product development within this role. Candidates must have a proven track record of shipping production-ready features, a robust command of the modern web stack, and essential, real-world, hands-on experience building and deploying with Large Language Models (LLMs) in a production environment.

Key Responsibilities

  • Rapid Prototyping and Production Deployment: Lead the prototyping, iteration, and deployment of sophisticated reader experiences powered by LLMs and content embeddings. This work will be conducted collaboratively with fellow engineers and a diverse group of cross-functional peers (including product managers and designers) from early concept stages through to full production release.
  • Full-Stack Development: Execute development across the entire application stack, utilizing robust Node.js/TypeScript for the backend services, React for dynamic and responsive front ends, and integrating advanced A.I. capabilities seamlessly across both layers.
  • Net-New A.I. Feature Integration: Build entirely new A.I. features and integrate them carefully into existing systems and APIs. A key component of this will be exercising sound judgment in determining when to build a component from scratch versus cleanly wiring together and leveraging established infrastructure.
  • Prompt Engineering as a Core Discipline: Write, rigorously test, and refine complex prompts and retrieval pipelines. You are expected to treat prompt engineering not as a minor task but as a first-class engineering discipline, vital for the success of A.I.-powered features.
  • Data-Driven Iteration: Thoroughly instrument all new features with comprehensive evaluations, crucial engagement signals, and detailed performance monitoring. Actively utilize this data to drive continuous improvement and optimization of the features.
  • Cross-Functional Collaboration: Work in close partnership with product managers, UX designers, journalists, and senior engineers to effectively translate complex editorial and journalistic goals into viable, high-quality working products.
  • Shaping Best Practices: Actively contribute to developing and maintaining shared organizational practices around feature evaluation, responsible A.I. usage, and defining what "good " product development looks like within an organization where editorial judgment and institutional independence are paramount and non-negotiable.

Minimum Requirements

  • Experience: 5-8 years of demonstrated, hands-on software engineering experience with a clear and established ability to ship impactful, consumer-facing features.
  • LLM Production Experience: Essential, hands-on experience building with Large Language Models within a real product context—going significantly beyond mere side projects or proof-of-concepts.
  • Full-Stack Command: Strong fundamental knowledge of the full web stack: demonstrated proficiency with Node.js or TypeScript on the backend and deep experience with React on the front end.
  • Technical Adaptability: Comfort and confidence navigating and contributing to unfamiliar or complex codebases and effectively working within established, often large-scale, backend infrastructure.
  • Product Instinct: A strong, innate product instinct; the ability to consistently think first and foremost about the end-user experience, not simply the technical implementation details.

Preferred Qualifications

  • System Integration Versatility: Experience working across both "greenfield " product development (building entirely new systems) and the challenging but rewarding integration with legacy systems or third-party APIs.
  • Python Proficiency: Additional backend experience in Python, particularly for building robust data pipelines, machine learning model integrations, or other data-intensive tasks.
  • Search and Personalization Expertise: Specific experience with advanced concepts such as semantic search, embedding-based retrieval systems, or sophisticated content personalization platforms.
  • Agentic Software Development: Experience building "agentic " software—systems where models are designed to plan, take actions, or operate across multiple, sequential steps; in this area, the complexity of the systems you've built matters more than mere professional tenure.
  • Evaluation and Testing Frameworks: Familiarity with evaluation frameworks tailored for A.I. features or significant experience with A/B testing methodologies in the context of machine learning applications.
  • Trust-Sensitive Product Background: A professional background working in complex, highly trust-sensitive product environments where deep editorial or institutional judgment fundamentally shapes the product development and release process.
  • Curiosity and Passion: A strong curiosity about the field of journalism and a genuine interest in the evolving future of how people consume and interact with information.

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