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Protocol Intelligence
Data-driven signals on your job's competitivenessSpecialized AI research role reduces pool, but Bengaluru metro and startup visibility increase applicant density.
Advanced ML and retrieval expertise transferable across AI product companies, but regulated-enterprise experience moderately preferred.
Many mandatory, specific AI production skills and tooling required, enforcing strict technical shortlisting.
Job Description
Structured overview of role & requirementsAbout This Role
Design and deliver AI systems that convert enterprise process knowledge and data into a governed, evidence-backed process ontology.
Build and maintain end-to-end pipelines for document ingestion, knowledge graph construction, retrieval engineering, and multi-agent orchestration frameworks.
Collaborate with product and research teams to define evaluation criteria and ensure continuous learning and improvement of AI-driven enterprise workflows.
Minimum Requirements
Proven experience delivering production-grade AI solutions in Python with strong typing, testing, and async pipeline design.
Deep expertise with large language model prompting, schema-driven extraction, retrieval techniques (dense embeddings, hybrid search, reranking).
Experience with property graph databases (e.g., Neo4j), entity resolution, GraphRAG pipelines, and multi-agent orchestration frameworks (e.g., LangGraph, OpenAI Agents SDK).
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Technical expert in AI-native software development focused on large-scale enterprise infrastructure for regulated environments.
Comfortable balancing ambitious research goals with product constraints and collaborating across product, engineering, and senior leadership.
Experienced in building governed, secure, evidence-backed AI systems operating at the intersection of enterprise knowledge management and automation.