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Tier-1 employer, mid-level AI role, Bangalore location, and generalist AI title attract strong applicant competition.
Core ML/LLM and cloud engineering skills transfer across industries, though legacy code modernization adds domain nuance.
Mandatory 4–7 years plus required cloud/AI certification and specific GCP/LLM/MLOps skills make filters strict.
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Architect, build, and deploy production-grade AI products to automate engineering workflows and accelerate software transformation.
Design intelligent systems using NLP and Large Language Models to modernize legacy codebases and technical documents.
Develop and optimize scalable AI microservices on Google Cloud Platform, ensuring performance, cost efficiency, and cross-functional integration.
4 to 7 years of experience in building, deploying, and scaling AI/ML products and generative AI applications.
Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Software Engineering, or related field.
Must hold at least one recognized cloud or AI certification (e.g., Google Cloud Professional Machine Learning Engineer).
Extensive expertise in Google Cloud Platform (GCP) services, including Vertex AI, Cloud Run, BigQuery, Cloud Functions, and GKE.
Experienced in end-to-end AI product lifecycle with strong skills in prompt engineering, model fine-tuning, and AI cost optimization.
Proficient in Python programming, code parsing (AST analysis), and MLOps including CI/CD pipelines and containerization (Docker, Kubernetes).
Capable of translating complex business requirements into scalable AI solutions with measurable impact and collaborating effectively with cross-functional teams.