Lead AI Architect - Data Platform

Banyan Software

9d•CA$180,000 - CA$210,000•Remote

About The Position

Banyan Software is hiring its first Lead AI Architect to design, build, and operate a centralized data and AI platform for the company. The platform will consolidate internal data into a governed AWS data lake and enable safe AI experimentation for functional teams such as Finance, M&A, and Business Development. The role is modeled on enterprise architecture for an AI-first environment: setting the target-state architecture and standard patterns while also writing code and owning outcomes. It partners closely with embedded business analysts and leaders across functional areas to ensure the platform addresses real use cases. This is a hands-on player-coach role initially, with the opportunity to build and lead a small platform team over time. The architect will establish the data lake, AI experimentation layer, data and security standards, and the operating model needed to keep the platform reliable as adoption grows. First-year goals include deploying a governed AWS data lake with at least three priority data domains, onboarding at least two functional verticals, documenting architecture and security standards, putting at least one AI use case into production, and hiring and ramping the first one or two team members. The position is remote and full-time. The role reports to the Head of AI and/or Head of IT. Compensation is CAD $180,000–$210,000 base, plus a performance bonus and benefits, with the final offer dependent on experience and qualifications.

Requirements

At least 10 years of experience building production data and AI platforms at meaningful scale.
Deep, hands-on AWS expertise, including S3, IAM, KMS, networking, Glue, Lake Formation, Athena, Redshift, SageMaker, Bedrock, and EKS or ECS.
Strong data architecture skills, including lakehouse patterns, open table formats such as Iceberg, Delta, or Hudi, data modeling, ingestion frameworks, orchestration, and lineage.
Experience with ingestion frameworks such as Fivetran, Airbyte, or custom solutions, and orchestration tools such as Airflow, Dagster, or similar.
Experience with modern AI/ML platform patterns, including feature stores, model registries, experiment tracking, prompt and evaluation frameworks, retrieval-augmented generation, and basic agentic workflows.
Working knowledge of AI safety practices, including data classification, PII handling, access tiering, evaluation, and model-risk controls.
Strong Python and SQL skills, and comfort with Terraform or AWS CDK.
Ability to read logs, resolve issues, and ship pull requests.
Player-coach experience leading small teams, mentoring engineers, setting hiring standards, and developing people.
Strong communication skills, including the ability to lead architecture decision reviews with engineers and explain trade-offs to executives.
Bachelor’s degree in computer science, engineering, or a related field.

Nice To Haves

Master’s degree.
Experience in private-equity-backed or holding-company environments with multiple business units and inconsistent source systems.
Experience designing AI guardrails for non-public, regulated, or competitively sensitive data.
Track record of treating internal platforms as products, with named users, SLAs, and an adoption strategy.
Experience with Snowflake or Databricks, particularly for bridging to portfolio-company data.
Experience as the first or an early platform hire at a growth-stage company.

Responsibilities

Define and own Banyan’s target-state data and AI architecture, documenting trade-offs and decisions.
Design and build an AWS-centric data lake, including patterns for storage, cataloging, querying, ingestion, modeling, and lineage.
Establish the AI experimentation layer, including model access through Anthropic, OpenAI, and other LLM providers.
Set data contracts, schema standards, naming conventions, and a domain model that can accommodate new data sources and acquired companies.
Partner with Senior Business Analysts in Finance, M&A, and Business Development to translate use cases into platform requirements and unblock their work.
Define security, privacy, and AI safety guardrails, including data classification, access tiering, and rules for handling PII, regulated data, and confidential portfolio information.
Remain hands-on by writing code, shipping infrastructure, conducting code reviews, and debugging production issues.
Build and develop the platform team, including vertical-aligned Senior Business AI Analysts; identify contractors for platform, ML platform, and data engineering work; and mentor team members.
Own platform reliability, observability, and cost, including setting SLOs, monitoring usage, and managing costs as the platform scales.
Represent Banyan’s AI and data architecture to executives, portfolio companies, and external partners.
Deliver a production-ready governed AWS data lake with at least three priority data domains landed and modeled.
Onboard at least two functional verticals with safe, audited access for analytics and AI experimentation.
Create a documented reference architecture, security model, and standards library.
Put at least one AI use case into production through the platform with monitoring, evaluation, and a clear ROI story.
Make and ramp the first one or two team hires.