You will get AWS SageMaker Cost + Security Audit
Project details
Most SageMaker environments have two problems
running simultaneously — they are overspending
and they are exposed. This engagement addresses
both in a single five-day audit.
What you get:
• Live dashboard — Cost, Security, and Executive
Overview tabs
• Exportable PDF findings report with severity
rankings across cost and security dimensions
• IAM policy review, endpoint exposure assessment,
and encryption audit
• Prioritized remediation roadmap
• Executive summary
• 60-minute findings walkthrough call
Delivered in 5 business days. Multi-account
coverage available on Standard and Advanced tiers.
running simultaneously — they are overspending
and they are exposed. This engagement addresses
both in a single five-day audit.
What you get:
• Live dashboard — Cost, Security, and Executive
Overview tabs
• Exportable PDF findings report with severity
rankings across cost and security dimensions
• IAM policy review, endpoint exposure assessment,
and encryption audit
• Prioritized remediation roadmap
• Executive summary
• 60-minute findings walkthrough call
Delivered in 5 business days. Multi-account
coverage available on Standard and Advanced tiers.
AI Development Type
Deep Learning, Model Tuning, Software MaintenanceAI Tools
Amazon SageMaker, Azure Machine Learning, MLflowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$4,000
|
Standard
$6,000
|
Advanced
$8,000
|
|---|---|---|---|
| Delivery Time | 5 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 2 |
AI Model Integration | - | - | - |
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | - |
Model Documentation | |||
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$500 - $750
Findings Presentation
(+ 1 Day)
+$250
Second AWS Account
(+ 2 Days)
+$500
Remediation support
(+ 2 Days)
+$750Frequently asked questions
About Jose
AI Engineer | LLM Apps, AWS, MLOps | Scalable & Cost-Efficient Systems
Las Vegas, United States - 5:03 am local time
I help companies build and scale AI systems that are reliable, secure, and cost-efficient from day one.
Whether you're building an LLM-powered app, deploying models on AWS, or fixing a system that isn’t performing as expected — I focus on making sure it actually works in real-world conditions.
What I can help you with:
• AI / LLM applications (RAG systems, chatbots, APIs)
• Backend development for AI systems (FastAPI, Django)
• Deploying and scaling models on AWS (SageMaker, ECS, EKS)
• MLOps pipelines (CI/CD, automation, monitoring)
• Performance optimization and cost control
• Securing AI systems (VPC, IAM, encryption)
Recent outcomes:
• Built and deployed scalable AI backends for production use
• Reduced infrastructure costs by 30–50%
• Reduced inference endpoint costs by 40% through autoscaling + right-sizing
• Improved performance and reliability of deployed systems
Tech stack:
Python, pandas, FastAPI, Django, AWS (SageMaker, Lambda, ECS, EKS, Bedrock), Terraform, Docker, PostgreSQL
If you're building an AI product and want it to actually scale and perform — I can help.
Happy to review your current setup and point out quick wins before any engagement.
Steps for completing your project
After purchasing the project, send requirements so Jose can start the project.
Delivery time starts when Jose receives requirements from you.
Jose works on your project following the steps below.
Revisions may occur after the delivery date.
Kickoff (Day 1)
45-minute call to confirm scope across accounts, priorities, and access requirements. You grant read-only IAM access using our setup guide — takes under 10 minutes per account to configure.
Environment Inventory (Day 1–2)
We inventory all SageMaker resources across your account(s) — endpoints, training jobs, notebook instances, pipelines, and supporting compute. CloudWatch utilization and CloudTrail data pulled for the preceding 30 days.