Description
Summary Role summary: We are looking for a senior AI Engineer to help build an AI-native intelligence platform for private markets. This person will own early product development across AI application logic, retrieval, model integration, and data workflows, and should be comfortable covering some initial ML engineering and data engineering tasks as the product matures. The ideal candidate is a strong builder who can move from prototype to production, work closely with product and domain experts, and help create the proprietary data flywheel that powers the platform. What you will build • AI-powered deal intelligence and market research workflows. • Retrieval systems that turn proprietary and licensed data into actionable answers. • Ranking, classification, matching, and summarization tools for private-market dealmaking. • Agentic features that help users discover deals, counterparties, pricing references, and market signals. • Data pipelines and feedback loops that improve system quality over time. Responsibilities • Design and build AI features for a private-markets intelligence platform. • Integrate foundation models, APIs, vector search, and retrieval workflows into production applications. • Build prompt, routing, and orchestration logic for AI-assisted workflows. • Implement evaluation frameworks for accuracy, relevance, latency, and reliability. • Work with structured and unstructured data from multiple sources. • Build initial data pipelines, schema definitions, and entity normalization where needed. • Support model experimentation, ranking logic, and lightweight fine-tuning or adaptation. • Instrument user behavior and feedback so every interaction improves the system. • Partner with product and domain stakeholders to define the highest-value wedge use case. • Ensure the system is secure, auditable, and suitable for institutional users. What we are looking for • 5+ years of experience in software engineering, ML engineering, AI engineering, or related roles. • Strong Python skills and experience building production systems. • Experience with LLM APIs, retrieval-augmented generation, vector databases, and workflow orchestration. • Familiarity with data pipelines, structured data modeling, and event instrumentation. • Ability to think in terms of product outcomes, not just technical implementation. • Comfort working in ambiguous, early-stage environments with fast iteration. • Experience with analytics, experimentation, logging, and evaluation. • Strong communication skills and good product judgment. Nice to have • Experience with private markets, fintech, market intelligence, or B2B workflow products. • Experience with entity resolution, knowledge graphs, ranking systems, or recommendation systems. • Experience with MLOps, deployment monitoring, and model versioning. • Experience handling sensitive, licensed, or compliance-heavy data. • Experience building internal tools, copilots, or AI agents. • Familiarity with FastAPI, PostgreSQL, vector search, cloud infrastructure, and modern backend stacks.