This role is for one of the Weekday's clients

**Salary range: Rs 2000000 - Rs 2500000 (ie INR 20-25 LPA)

**Min Experience: 1 years

Location: Bengaluru

JobType: full-time

The Junior GenAI Engineer will focus on developing the AI components of the product, including CS Copilot (real-time call intelligence), LLM-powered document understanding, and AI-driven feature pipelines. This position entails creating authentic AI-integrated systems with guidance from senior engineers, with the goal of independently managing AI features end-to-end within 12-18 months. The ideal candidate should have a solid engineering background and the capability to incorporate AI into a production codebase with minimal supervision.

Key Responsibilities

Develop the AI layer of the company’s product, such as CS Copilot, LLM-powered document understanding, and AI feature pipelines
Implement AI integration within a production-level codebase
Progress to full ownership of AI features from start to finish within 12-18 months
Construct genuine AI-integrated systems and analyze their failure modes to prevent recurring errors

Qualifications

1.5 to 4 years of professional full-time software development experience (internships excluded)
Strong foundational engineering skills, including at least basic backend expertise
Demonstrated experience building real AI-integrated systems, beyond simple API wrappers or tutorials
Experience incorporating AI into actual data workflows rather than isolated scripts
Understanding of AI failure modes (e.g., hallucinations, irrelevant responses, latency issues) and strategies for mitigation
Ability to perform basic evaluation or quality assessments of AI outputs (such as manual tests, human reviews, or accuracy validations)
Proficiency in Python for backend development; familiarity with FastAPI, Django, Go, or Node.js is highly desirable
Experience deploying or hosting AI services, including cloud functions or containerized environments
Record of self-driven AI projects or contributions beyond formal job duties or academic coursework
Publicly visible technical contributions (e.g., GitHub repositories with substantial AI projects, technical blogs, Kaggle or Hugging Face involvement)
A demonstrable trajectory of growth in AI system development, extending beyond basic API utilization

Skills

Python, FastAPI, Django, Node.js, REST API, PostgreSQL, Cloud Deployment, Containerization, LLM Integration, RAG Systems, AI Feature Pipelines, Data Flow Integration, AI Evaluation, Open Source Contribution