AI Engineer

Overview

AI Engineer responsible for architecting, building, and deploying production-grade AI products that automate engineering workflows, modernize software, and support intelligent enterprise platforms.

What you'll do

• Lead AI product lifecycles from architecture and model selection through deployment, monitoring, and optimization.
• Design NLP and LLM systems to parse, translate, and modernize legacy code and technical documentation.
• Develop prompt architectures, RAG pipelines, and fine-tuned models for domain-specific artifact generation.
• Build scalable AI microservices and batch pipelines on Google Cloud Platform.
• Establish CI/CD pipelines, automated testing, API designs, and technical documentation.
• Monitor and optimize AI inference costs, token spend, vector queries, and GPU/TPU utilization.
• Mentor junior engineers and collaborate with product, design, architecture, and domain teams.

What you'll need

• 4–7 years of hands-on experience building, deploying, and scaling end-to-end AI/ML products.
• Bachelor’s or Master’s degree in a relevant quantitative or computing field.
• At least one recognized cloud or AI certification.
• Extensive Google Cloud Platform experience, including Vertex AI, Cloud Run, BigQuery, Cloud Functions, and GKE.
• Strong proficiency with LLMs, RAG, vector databases, LangChain, or LlamaIndex.
• Mastery of Python and proficiency with APIs, gRPC, microservices, and modern frontend frameworks.
• Hands-on MLOps, Docker, Kubernetes, model tracking, testing, and CI/CD experience.

Nice to have

• Experience with source-to-source compilers, code conversion, or automated design document generation.
• Familiarity with legacy enterprise frameworks and multi-language code conversion.
• Quantitative product analytics experience.
• Active GitHub profile or portfolio demonstrating end-to-end AI applications.

Details

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