Teams at Neurons Lab

Leads enterprise AI adoption programs from assessment through workshops, hands-on enablement, adoption measurement, and team self-sufficiency. Builds client relationships, develops internal AI champions, creates reusable prompts and templates, ensures compliance with data-governance and responsible-AI policies, reports business impact and ROI, and identifies expansion opportunities. The role requires practical AI fluency, strong facilitation, change-management expertise, customer success capabilities, and executive communication skills.

Build unstructured-data ingestion and context-layer pipelines for an investment group. Responsibilities include historical backfills, document parsing, entity resolution, deduplication, incremental API synchronization, embeddings, vector and graph storage, access scoping, lineage, PII protection, orchestration, monitoring, cost control, and operational runbooks.

Client-facing AI Analyst responsible for eliciting executive strategy, OKRs, investment policies, and operating processes; defining AI agent skills and evaluations; interpreting process-mining data; modeling ROI; prototyping LLM solutions; driving executive adoption; and documenting requirements, decisions, and runbooks. The role partners with executives, an AI Architect, and a Data Engineer to deliver an AI context layer and executive pilot.