Lead AI Architect - Data Platform

A production-ready, governed data lake foundation deployed on AWS, with at least three priority data domains landed and modeled.

At least two functional verticals onboarded to the platform with safe, audited data access for analytics and AI experimentation.

A documented reference architecture, security model, and standards library that new use cases and new hires can plug into.

At least one AI use case running in production through the platform, with monitoring, evaluation, and a clear ROI story.

First one to two team hires made and ramped.

10+ years building data and AI platforms in production at meaningful scale. You have shipped, not just diagrammed.

Deep AWS expertise. Hands-on with S3, IAM, KMS, networking, Glue, Lake Formation, Athena, Redshift, SageMaker, Bedrock, and EKS or ECS.

Strong data architecture chops: lakehouse patterns, open table formats (Iceberg, Delta, or Hudi), data modeling, ingestion frameworks (Fivetran, Airbyte, custom), orchestration (Airflow, Dagster, or similar), and lineage.

Real experience with modern AI/ML platform patterns: feature stores, model registries, experiment tracking, prompt and evaluation frameworks, retrieval-augmented generation, and basic agentic workflows.

A working point of view on AI safety: data classification, PII handling, access tiering, evaluation, and model-risk controls.

Hands-on coder. Strong Python and SQL. Comfortable in Terraform or AWS CDK. Reads logs, fixes issues, ships pull requests.

Player-coach experience. You have led small teams, mentored engineers, set hiring bars, and grown people.

A strong communicator. You can drive an architecture decision review with engineers and explain trade-offs to executives in the same week.

Bachelor's degree in computer science, engineering, or a related field. A master's degree is a plus, not a requirement.

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 a real adoption strategy.

Experience with Snowflake or Databricks. Useful when bridging to portfolio company data without forcing a single stack.

Past experience as the first or early platform hire at a growth-stage company.

Greenfield with real budget. You set the foundation, you do not inherit a tangle.

Real ownership of the AI and data architecture for an entire holding company.

A long-term horizon. We do not optimize for the next quarter, so the platform you build can compound.

A team that treats AI as a serious capability, not a buzzword. We have already built internal AI tooling we use every day.

A culture of accountable autonomy. We trust you to do the work.

Competitive compensation, benefits, and meaningful long-term upside.

Team

AI & Data Science

Reports to

Head of AI (And Or) Head of IT

Scope

Player-coach. Hands-on architect today, leading a small platform team over time.

Send your resume and a short note describing a data or AI platform you have architected. Tell us the choices you made, what shipped to production, and what you would do differently if you were starting over today.

We look forward to hearing from you.

Diversity, Equity, Inclusion & Equal Employment Opportunity at Banyan: Banyan affirms that inequality is detrimental to our Global Teams, associates, our Operating Companies, and the communities we serve. As a collective, our goal is to impact lasting change through our actions. Together, we unite for equality and equity. Banyan is committed to equal employment opportunities regardless of any protected characteristic, including race, color, genetic information, creed, national origin, religion, sex, affectional or sexual orientation, gender identity or expression, lawful alien status, ancestry, age, marital status, or protected veteran status and will not discriminate against anyone on the basis of a disability. We support an inclusive workplace where associates excel based on personal merit, qualifications, experience, ability, and job performance.

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