Lead AI Architect - Data Platform
Banyansoftware · United States
About this role
## Lead AI Architect — Data Platform ### About Banyan Software Banyan Software is a permanent home for software businesses serving specialized industries. With a buy-grow-and-hold-for-life approach and a permanent capital base, Banyan acquires and grows companies worldwide—honoring founder legacies and helping portfolio companies modernize through shared AI expertise and operational discipline. Founded in 2016, Banyan operates 120+ portfolio companies across North and South America, Europe, and APAC, and has appeared on the Inc. 5000 list for six consecutive years. The Banyan Software Foundation (endowed with $100M in Banyan stock) leverages technology to build a greener and more equitable world. --- ### The Role We’re hiring our **first Lead AI Architect** to design, build, and run the **centralized data and AI platform** that powers Banyan. The cornerstone of the work is a **centralized data model** and **Banyan data lake** that consolidates existing data and enables **safe AI experimentation** for internal functional teams (Finance, M&A, Business Development, and others). This role is modeled on a classical **Enterprise Architect** role—adapted for an **AI-first world**. You’ll set the target-state architecture, choose standardized patterns, write code yourself, and **own the outcome**. You’ll partner with embedded business analysts and functional leaders to ensure the platform stays grounded in real use cases. This is a **player-coach** role: you start hands-on, and over time you build and lead a small platform team. --- ### What You Will Build - **A centralized data lake on AWS**: the single, governed source of truth for internal Banyan data—designed for analytics, ML, and AI experimentation. - **A reference architecture for AI**: standardized patterns and building blocks to go from idea to safe production (model selection, RAG, evaluation, observability, cost controls). - **Guardrails for safe experimentation**: data classification, access tiering, sandboxes, audit logging, and clear rules for what can be sent where. - **A platform team and operating model**: standards, rituals, and practices that keep the platform reliable and improving as adoption grows. --- ### What You Will Do - Define and own Banyan’s **target-state data and AI architecture**, making trade-offs explicit. - Design and build the **AWS-centric data lake** (storage, cataloging, query, ingestion, modeling, lineage). Likely stack includes **S3, Glue, Lake Formation, Athena, Redshift, Iceberg (or similar)**, plus **Terraform or CDK**. - Stand up the **AI experimentation layer**, including model access via **Anthropic, OpenAI**, and other LLM providers. - Establish **data contracts**, schema standards, naming conventions, and a domain model that scales as sources grow and companies are acquired. - Partner with embedded **Senior Business Analysts** in Finance, M&A, and Business Development to translate use cases into platform requirements. - Define **security, privacy, and AI safety guardrails** (PII handling, regulated data, confidential portfolio information). - Stay hands-on: write code, ship infrastructure, run code reviews, and debug production issues. - Build the team (including vertical-aligned Senior Business AI Analysts) and set engineering quality standards. - Own **reliability, observability, and cost**: set SLOs, monitor usage, and keep spend rational as you scale. - Represent Banyan’s AI and data architecture to executives, portfolio companies,
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