AI Fullstack Engineer

About Us

DeepReach AI is building the next generation of AI-driven data annotation infrastructure to power the world’s most advanced AI models. Our mission is to combine human expertise with AI automation to make high-quality labeled data faster, cheaper, and more scalable. As an early-stage startup, we move fast, take ownership, and iterate relentlessly.

Role Overview

We are seeking a Fullstack Engineer with strong AI integration experience to join our founding technical team. You will help design and implement a scalable, high-performance data annotation platform capable of supporting 500+ concurrent annotators working seamlessly, with deep AI model integration to enhance productivity and accuracy.

You will be working across the frontend, backend, and AI service layers, collaborating directly with the founders to define the technical architecture and ship production-ready features.

Key Responsibilities

• Design and build a scalable, real-time data annotation platform that supports hundreds of concurrent users.
• Integrate AI models (LLMs, CV models, NLP pipelines) into the annotation workflow to accelerate and improve labeling quality.
• Implement real-time collaboration features, task distribution, and performance monitoring.
• Optimize system performance for speed, reliability, and cost-efficiency.
• Collaborate with the team on technical architecture, DevOps, and deployment strategies.
• Maintain security best practices for user data and annotation projects.

Requirements

• 5+ years of experience in fullstack development, ideally with production-scale SaaS platforms.
• Strong backend experience with Node.js, Python, or Go, and cloud environments (AWS preferred).
• Proficient with modern frontend frameworks such as React, Next.js, or Vue.js.
• Experience with real-time systems (WebSockets, WebRTC, or similar).
• Familiarity with AI/ML model integration and serving pipelines.
• Experience with relational and NoSQL databases (e.g., PostgreSQL, DynamoDB).
• Ability to work independently in a fast-paced, ambiguous startup environment.

Nice to Have

• Experience building collaborative tools or marketplaces.
• Prior work on annotation platforms, crowdsourcing systems, or workforce management tools.
• Familiarity with MLOps tools for deploying and maintaining AI models.

What We Offer

• Opportunity to join a startup at the ground floor with founding-team equity.
• Work on cutting-edge AI products that directly shape the future of AI training data.
• Flexible, remote-friendly work environment with a high degree of autonomy.
• Direct collaboration with founders and industry experts.