AI Engineer

Overview

AI Engineer role focused on architecting, building, and deploying production-grade AI/ML and generative AI products for enterprise use.

What you'll do

• Lead the end-to-end lifecycle of AI products from design and model selection to production deployment and monitoring.
• Build intelligent automation and modernization systems using NLP and LLMs to parse and modernize legacy code and documentation.
• Develop prompt architectures, RAG pipelines, and fine-tuned models for domain-specific artifact generation and technical decision support.
• Implement GCP-based AI microservices and batch processing pipelines for scalability and reliability.
• Set up CI/CD pipelines for AI assets, automated testing, robust API design, and technical documentation.
• Monitor and optimize inference and operational costs using token metering and cost-attribution frameworks.

What you'll need

• 4 to 7 years of hands-on experience building, deploying, and scaling end-to-end AI/ML products and generative AI applications.
• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, AI, Data Science, or Software Engineering.
• At least one recognized cloud or AI certification (e.g., Google Cloud Professional Machine Learning Engineer or equivalent).
• Extensive expertise in Google Cloud Platform (GCP) including Vertex AI, Cloud Run, BigQuery, Cloud Functions, and GKE.
• Strong proficiency with LLMs, RAG architectures, vector databases (e.g., Pinecone, ChromaDB, Vertex Vector Search), and frameworks like LangChain or LlamaIndex.
• Mastery of Python and solid proficiency in backend/web stacks (e.g., RESTful APIs, gRPC, microservice patterns, modern frontend frameworks).
• Hands-on MLOps/DevOps experience including CI/CD pipelines, containerization (Docker, Kubernetes), and automated testing.

Details

• Location: Bangalore Area.
• Employment type: Permanent.