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Protocol Intelligence
Data-driven signals on your job's competitivenessStrong Tier-1 brand and metro location increase applicants, but seniority and niche LLM specialization moderate competition.
Specialized LLM/NLP and production ML skills transfer across industries, but finance domain preference raises sensitivity.
Explicit 15+ years and deep NLP/LLM production requirements create very strict technical filters.
Job Description
Structured overview of role & requirementsAbout This Role
Lead end-to-end development and deployment of autonomous AI agents and NLP models, ensuring scalable, production-ready systems.
Design and implement Retrieval-Augmented Generation pipelines and LLM-powered applications over structured enterprise data for advanced querying and insights.
Maintain and enhance evaluation tools to monitor performance, reliability, and consistency of large language models throughout their lifecycle.
Minimum Requirements
5-6 years of experience in NLP / AI Data Science as explicitly mentioned in the JD.
Bachelor's degree or higher in Machine Learning, Computer Science, Computational Linguistics, Data Engineering, or related technical field.
Proven experience with autonomous agent systems, multi-step reasoning, and LLM application development on structured/tabular data.
Experience with RAG architectures, embedding generation, vector databases such as FAISS, Pinecone, Weaviate, or pgvector.
Ideal Candidate Profile
Experienced in building and deploying autonomous agentic AI systems involving planning, tool use, and feedback loops, demonstrating advanced strategic AI skills.
Hands-on ability to collaborate across data engineering and platform teams to ensure reliable AI data pipelines, indicating strong operational execution in enterprise settings.
Comfortable communicating complex technical concepts to diverse audiences, showing capability in cross-functional stakeholder engagement.