Overview

# Data Scientist / AI/ML Engineer / GenAI Engineer

Responsibilities

• Design scalable and reliable AI systems with a focus on production readiness, maintainability, and performance.
• Develop, deploy, and maintain production AI/ML applications.
• Build and maintain **RAG pipelines and AI agent frameworks**.
• Design reliable LLM workflows using structured outputs, validation, retrieval, and business rules.
• Perform data analysis, model evaluation, debugging, and performance optimization.
• Develop APIs and integrate AI solutions with existing products and platforms.
• Develop automated evaluation, validation, and testing strategies for AI applications.
• Perform root cause analysis and troubleshoot AI pipelines to improve accuracy, consistency, and reliability.
• Monitor and continuously improve deployed AI systems.
• Collaborate with engineering and business teams to define AI use cases and deliver solutions.

Qualifications

• CTC:** ₹15–25 LPA
• Notice Period:** 0–30 Days
• 3–4 years of experience in AI/ML application development
• *Strong Python**
• Strong software engineering fundamentals
• AI system design, evaluation, monitoring, and performance optimization
• Production AI application development and deployment
• Clean code, modular design, debugging, and testing
• *RAG Architectures**
• TensorFlow / PyTorch / Scikit-learn
• NLP concepts
• API development and integration
• Ability to work independently and collaboratively
• Vector Databases: **Pinecone, Weaviate, FAISS, ChromaDB**
• Cloud: **AWS, Azure, GCP**
• Docker and deployment pipelines
• FinTech domain experience
• Assessment / Test
• Technical Round
• Technical Round
• Business Head Interview
• HR Round
• Office Hours:** 9:00 AM – 6:00 PM
• Interview Availability:** 10:00 AM – 5:00 PM
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related quantitative field.