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Tier-1 brand, mid-level 2–4 years, Bangalore metro, and broad GenAI skillset increase applicant competition.
Role requires specialized GenAI, LLM and data engineering expertise, limiting transferability across non-ML domains.
Explicit 2–4 years, minimum 2 years GenAI, plus mandatory LLM and Databricks/Spark skills enforce high strictness.
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Design, develop, and deploy Generative AI (GenAI) solutions focusing on production readiness and data scalability.
Build and scale Retrieval-Augmented Generation (RAG) systems and integrate with graph-based memory and multi-agent frameworks to enhance Large Language Model (LLM) capabilities.
Collaborate with data scientists and ML engineers to integrate GenAI models with data infrastructure, ensuring system scalability, reliability, and maintainability.
2 to 4 years of total experience in AI/ML, software engineering, or data engineering with at least 2 years hands-on in GenAI systems development.
Strong proficiency in Python for AI development and data engineering tasks.
Experience with Databricks, Spark, and cloud-native data platforms such as Delta Lake.
Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or related fields.
Experienced in working with advanced GenAI technologies including LLMs (e.g., GPT-4, Claude 2, Gemini) and multi-agent orchestration frameworks (e.g., LangChain, AutoGen, LangGraph).
Skilled in software engineering best practices such as version control, testing, and CI/CD applied to AI/ML pipelines.
Capable of handling scalable production AI systems integrating data engineering tools and ensuring reliability in enterprise environments.