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Strong SaaS brand and Bengaluru metro increase competition, but niche agentic AI expertise limits candidate pool.
Medium — LLM and production ML skills transfer across industries, but revenue-focused agentic expertise adds specificity.
High — explicit 6–8 years plus mandatory agentic AI, NLP, and production ML experience required.
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Rapid prototyping and building of agentic AI solutions such as auto-summarization, CRM updates, and RAG pipelines for revenue-related applications.
Ship production-quality Python code from prototypes and partner with engineering to deploy and maintain AI models and agents.
Own evaluation processes for AI work including offline evaluations, LLM-judging, and regression tracking to ensure performance and reliability.
6-8 years total experience with at least 2-3 years hands-on building agentic AI systems including LLM-based inference, retrieval-augmented generation (RAG), and agents.
2-3 years experience in core NLP/data science including text classification, NER, embeddings, and feature engineering before agentic AI work.
Proficient in production-grade Python and SQL coding practices with testing, typing, and engineering workflows (Git, Docker, CI/CD).
Hybrid work ability with mandatory onsite presence in Bengaluru, India; candidates must be based in India.
Strong execution-oriented builder with experience rapidly turning ambiguous AI problems into prototypes and production systems without heavy managerial oversight.
Depth in both classical NLP/ML methods and modern LLM/agent frameworks, able to judiciously select appropriate approaches.
Experienced collaborator closely partnering with engineering teams on deployment, evaluation gating, and risk flagging in production environments.