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Lead AI Architect - Data Platform

Ban*** · Seattle, WA, United States
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Seattle, WA, United States180,000-240,000 USD/yearlyOnsite
Remuneration
180,000-240,000 USD/yearly
Location
Seattle, WA, United States
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Job summary

Ban*** is the best permanent home for software businesses that serve specialized industries, their employees, and their customers. We are on a mission to acquire, build, and grow great companies worldwide, helping them modernize through shared AI expertise and operational discipline.

Benefits

And meaningful long-term upside.Quick FactsTeam: AI & Data ScienceReports to: Head of ITScope: Player-coach.Hands-on architect today, leading a small platform team over time.Type: Full-timeLevel: LeadCompensation: Competitive base of CAD $180,000 to $240,000 plus performance bonuFinal offer reflects experience and

Qualifications

  • and to unblock their work.
  • Define security, privacy, and AI safety guardrails.
  • Classify data, design access tiering, and set the rules for handling PII, regulated data, and confidential portfolio information.
  • Stay hands-on.
  • Write code, ship infrastructure, run code reviews, and debug production issues.
  • Architects who do not build lose touch.
  • Build the team including vertical aligned Senior Business AI Analysts.
  • Find suitable contractors for data platform engineers, ML platform engineers, and data engineers.
  • Mentor them.
  • Set the bar for engineering quality.
  • Own platform reliability, observability, and cost.
  • Set SLOs, monitor usage, and keep the bill rational as we scale.

Responsibilities

  • You will set the target-state architecture, choose the patterns we standardize on, write code yourself, and own the result.
  • You will partner with our embedded business analysts and the leaders of each functional vertical so the platform stays grounded in real use cases, not abstractions.
  • What You Will Build
  • Define and own the target-state data and AI architecture for Banyan.
  • Make the trade-offs explicit and write them down.
  • Design and build the AWS-centric data lake.
  • Set the patterns for storage, cataloging, query, ingestion, modeling, and lineage.
  • Likely stack: S3, Glue, Lake Formation, Athena, Redshift, Iceberg or similar open table formats, plus Terraform or CDK for infrastructure as code.
  • Stand up the AI experimentation layer: model access via Anthropic, OpenAI and other LLM
  • Establish data contracts, schema standards, naming conventions, and a domain model that holds up as we add sources and acquire companies.
  • Partner with our Senior Business Analysts embedded in Finance, M&A, and Business Development to translate use cases into platform

Skills

Excel

Degrees

AssociateBachelorDegreeMaster

Industry

AutomotiveBankingEnergy

Company size

EnterpriseScaleupSmb

Security clearance

Confidential