Back
Tier-1 employer, mid-level role in metro Bangalore with sought-after GenAI skills increases competition.
Core ML, GenAI and MLOps skills are transferable, though regulated-compliance experience is beneficial.
Explicit 4–6 years and many mandatory GenAI, MLOps, cloud and vector DB requirements increase strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and deploy AI/ML models and architect scalable Retrieval-Augmented Generation (RAG) pipelines using LangChain, LangGraph, and vector databases across AWS, Azure, and GCP.
Design and implement Agentic AI workflows for autonomous decision-making, including multi-agent collaboration and fallback strategies.
Manage end-to-end ML lifecycle including data pipelines, feature stores, MLOps practices, and CI/CD pipelines ensuring security and compliance with standards like GDPR and HIPAA.
4–6 years of experience in AI/ML development, backend services, and Generative AI applications.
Strong proficiency in Python, LangChain, LangGraph, vector databases (FAISS, Pinecone, Weaviate), and cloud AI services (AWS, Azure, GCP).
Bachelor's or Master's degree in Computer Science, Data Science, or related field.
Location: Bangalore-based with willingness to travel within India and globally.
Technical decision-maker capable of evaluating trade-offs across performance, scalability, robustness, and cost within assigned components.
Proven hands-on experience building production-grade GenAI and Agentic AI solutions leveraging multi-cloud environments and orchestration frameworks.
Experienced working under organizational guidelines with independent ownership of complex AI/ML system components.