Zenith Cloud Consulting | AWS Data & AI Architect

Why Companies Choose to Work with Me

What sets my engagements apart

Cuts Through Complexity

I find the shortest path from ambiguity to production. While others are still mapping requirements, I've already built the first iteration.

Force Multiplier

I don't just deliver a solution - I raise the bar for your entire team. Every engagement leaves behind better patterns, sharper skills, and infrastructure your people actually understand.

Bias for Action

I ship solutions, not slide decks. While others are still in meetings, the infrastructure is already running.

./THE_ARCHITECT

Tim Schill

Founder & Principal Architect

I build AWS platforms at the intersection of data, AI, and security. Where most consultants draw architecture diagrams, I ship production systems - bridging the gap between DevOps and Data Science so that complex requirements become running infrastructure.

At Zenith Cloud Consulting, I don't just advise. I architect and build. My approach transforms fragmented data lakes and "Shadow AI" initiatives into governed, scalable, multi-tenant platforms that drive real business value.

Credentials

>> AWS Certified Security – Specialty
>> AWS Certified Solutions Architect
>> AWS Agentic AI Demonstrated

Tim Schill - Founder & Principal Architect at Zenith Cloud Consulting

Core Services

01_GEN_AI

Enterprise GenAI

I design and deliver GenAI platforms for regulated enterprises - from secure RAG architectures and AI Gateways to agentic AI solutions. Battle-tested in financial services, built for production.

Bedrock AgentCore SageMaker RAG MCP Guardrails

02_DATA_PLATFORM

Modern Data Platform

AWS-native data platforms built as internal products. Self-service APIs that let tenants govern their own data - from access control to provisioning - without bottlenecking your platform team. Scalable, secure, multi-tenant by design.

Lake Formation Glue Step Functions Iceberg Athena S3

03_PLATFORM

Platform Engineering

Cloud foundations that let your organization move fast without breaking governance. Landing zones, account vending, data perimeters, and security baselines - designed so every team gets a secure, production-ready environment on day one. Infrastructure as Code throughout, from Terraform modules to CI/CD automation.

Terraform EKS Lambda Control Tower CDK SCP / RCP

Validated Architectures

BLUEPRINT_ALPHA

Federated GenAI Hub

Your business units are already using AI - the question is whether you govern it or chase it. The Federated GenAI Hub gives every team a secure, metered path to foundation models through a centralized AI gateway, eliminating Shadow AI while letting innovation happen at the edge.

Model abstraction - single API, swap providers without code changes

Zero internet exposure - all traffic via PrivateLink

Centralized guardrails, content policies, and compliance controls

Full audit trail - every invocation logged for regulatory compliance

Per-tenant cost governance with budgets and chargeback

Agent governance - control agentic workflow access and execution

Bedrock AgentCore PrivateLink Guardrails CloudWatch MCP

BLUEPRINT_BETA

Self-Service Data Mesh

A multi-tenant data platform where domain teams register, share, and govern their own data products - without waiting on a central platform team. Built on AWS-native services with Apache Iceberg as the open table format.

Data product self-service - register datasets via API with automated cataloging

Apache Iceberg on S3 - time-travel, schema evolution, engine-agnostic access

Fine-grained access via Lake Formation tags, S3 policies, and VPC endpoints

Unified governance API for permissions, KMS grants, and tenant onboarding

Tenant workload autonomy - run Glue jobs within platform-enforced guardrails

End-to-end data lineage via Glue catalog metadata

Lake Formation Glue Iceberg Athena S3 KMS Step Functions API Gateway

BLUEPRINT_GAMMA

SageMaker ML Platform

A unified data and AI platform built on SageMaker Unified Studio, with project-based isolation, standardized MLOps pipelines, and built-in governance across data, models, and GenAI. Your teams ship production models and AI applications - not infrastructure.

Unified Studio workspace with per-project IAM and cost allocation

Lakehouse on Iceberg - S3, Redshift, and Feature Store unified

MLOps pipelines with MLflow tracking and Model Registry

Built-in governance, lineage, and responsible AI via Clarify

Continuous monitoring with automated retraining pipelines

Secure-by-design - VPC-only, PrivateLink, KMS, delivered via CDK/Terraform

SageMaker Pipelines Feature Store Model Registry Step Functions ECR CloudWatch CDK

Architecting the Future of
Data & AI on AWS