AI Application Engineer

AI Applications Engineer – Annotation Tooling and Data Operations

About KGeN / KAI

KGeN’s “KAI – Training & Evaluation” business taps a network of 1M+ verified experts across 60+ countries and 20+ languages, delivering specialised datasets across domains such as coding, STEM, healthcare, content, design, legal and general data collection and labeling power large‑language and multimodal AI systems.

KGeN is one the fastest growing startups with revenue growth to $50M+ ARR within 3 years. Funded by the most marquee investors - Accel, Prosus, Sequoia, Nexus and Lightspeed.

Role Overview

You will design, develop, and deploy intelligent tooling and systems that enhance the efficiency of KAI’s GenAI operations. Your work will focus on automating human-in-the-loop (HITL) pipelines, improving data labeling and evaluation workflows, and leveraging AI / ML to optimize annotation quality, routing, and workforce productivity. This role is ideal for engineers passionate about combining applied ML, backend systems, and data infrastructure to improve real-world AI training at scale.

Key Responsibilities

1. Build the Multimodal AI Annotation Platform

• Architect and develop a modular annotation system supporting images, audio, video, and text.
• Integrate open-source frameworks (Label Studio, CVAT, Diffgram, Whisper, Pyannote, MediaPipe, Rekognition, Vertex AI, etc.) with custom logic for quality control, automation, and AI-assist.
• Implement APIs and SDKs to manage data ingestion (S3 / GCS), task creation, and result exports.
• Build a human-in-the-loop QC pipeline combining auto-validation and reviewer workflows.
• Create and maintain ML backend services for AI-assisted labeling using existing or custom models.

2. Build Products that Convert Customer AI Needs into Solutions

3. Integrate AI and MLOps Stack

Required Skills and Experience

Experience

4–8 years of experience in full-stack or AI application development, with 2+ years in ML or AI-powered

systems

Programming

Strong in Python , Node.js , and cloud-native development (FastAPI, Flask, Express)

AI Tools

Experience integrating vision, audio, and NLP models (AWS Rekognition, OpenAI Whisper, Pyannote, Hugging Face Transformers, Vertex AI, etc.)

Data Annotation / QC Tools

Hands-on with Label Studio , CVAT , Diffgram , or similar OSS platforms; experience extending them via API / SDK

Cloud Platforms

Proficient in AWS or GCP (S3 / GCS, Lambda / Cloud Functions, API Gateway, Cloud Run)

Front-end

Familiarity with React / Next.js / Retool / Streamlit for internal dashboards

Databases

PostgreSQL, DynamoDB, or Firestore; experience designing schema for annotation / QC metadata

DevOps

Docker, CI / CD, environment management, API versioning

AI Systems Thinking

Ability to design scalable, multimodal pipelines combining automation + human review

Soft Skills

Ownership, clarity in communication, user empathy, ability to lead cross-functional efforts

Nice-to-Have Skills

Who You Are

What we offer

For any questions, please write us at apurva@kgen.io