AWS Cloud Infrastructure Architect

MACHINE LEARNING TECHNOLOGIES LLC; Frisco (TX); On-site; USD 124,000 - 220,000; Full time

Job summary

Machine Learning Technologies LLC is seeking an AWS Cloud Infrastructure Architect in Frisco, TX to lead end-to-end cloud infrastructure design and migration efforts. The role focuses on multi-account landing zones, secure networking, and container platforms using EKS and Kubernetes at scale.

Ideal candidates bring 8+ years in cloud architecture with deep AWS expertise, strong governance and security experience, and leadership capabilities.

Qualifications

• 8+ years of experience in Cloud Architecture, Infrastructure Engineering, or Platform Engineering.
• 5+ years of advanced AWS experience across EC2, VPC, IAM, EKS, RDS, Route53, S3, CloudWatch, CloudTrail, Config, and related services.

Responsibilities

• Architect end-to-end infrastructure solutions leveraging AWS Well-Architected Framework and enterprise design patterns.
• Design scalable, secure multi-account landing zones, VPC architectures, enterprise networking, and workload isolation strategies.
• Provide architecture leadership for containerized platforms, including Amazon EKS and large-scale self-managed Kubernetes clusters.
• Lead complex On-Prem AWS migrations and intra-AWS migrations with account realignments and multi-region moves.

Skills

AWS cloud architecture

Kubernetes

Terraform

Security & compliance

Multi-account governance

Leadership

Communication

Tools

Terraform (IaC)

EKS

Networking

Job description

Job Description

Job Overview

Job ID

J52801

Job Title

AWS Cloud Infrastructure Architect

Location

Frisco, TX

Duration

24 Months + Extension

Hourly Rate

Depending on Experience (DOE)

Work Authorization

US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, L2-EAD, GC-EAD

Client

To Be Discussed Later

Employment Type

W-2, 1099, C2C

Key Responsibilities

• Architect end-to-end infrastructure solutions leveraging AWS Well-Architected Framework and enterprise design patterns.
• Design scalable, secure multi-account landing zones, VPC architectures, enterprise networking, and workload isolation strategies.
• Provide architecture leadership for containerized platforms, including Amazon EKS and large-scale self-managed Kubernetes clusters.

Migration Leadership

• Lead complex On-Prem AWS and intra-AWS migrations involving VPC redesigns, account realignments, multi-region moves, and host architecture changes.
• Drive migrations from shared-tenant EC2/EKS deployments to AWS Dedicated Hosts, ensuring compliance, performance, and workload isolation.
• Conduct infrastructure assessments, migration strategies (rehost, replatform, refactor), and detailed cutover planning.

AWS Dedicated Host Expertise

• Design and manage workloads running on AWS Dedicated Hosts, including host allocation, tenancy planning, compliance alignment, and lifecycle management.
• Optimize compute planning, licensing models, capacity strategies, and high-availability architectures using Dedicated Hosts.
• Ensure secure and compliant hosting for sensitive workloads requiring physical isolation and regulatory controls.

Kubernetes & Platform Engineering

• Architect and manage large, multi-cluster Kubernetes environments with enterprise-grade reliability and security.
• Define compute and scaling strategies using EC2, EKS, Bottlerocket, autoscaling groups, and Dedicated Hosts backed node groups.
• Implement service mesh, workload identity, observability architectures, and cluster lifecycle automation.

Governance, Security & Compliance

• Develop and enforce IAM architectures, guardrails, cloud governance, and security policies aligned with CIS, NIST, and organizational standards.
• Partner with Security and Compliance teams to implement hardening, encryption, network segmentation, and threat detection.

Operational Excellence

• Lead performance tuning, capacity planning, resiliency engineering, and availability design for large-scale AWS workloads.
• Define operational playbooks for deployments, monitoring, backups, DR/HA, and workload lifecycle management.
• Mentor engineering teams on AWS architecture patterns, DevOps practices, and migration execution.

Cross-Functional Leadership

• Serve as a trusted advisor to engineering, SRE, product, and executive leadership.
• Partner with AWS teams and vendors to drive best practices and architectural decisions.
• Communicate complex solutions clearly to both technical and non-technical audiences.

Required Qualifications

• 8+ years of experience in Cloud Architecture, Infrastructure Engineering, or Platform Engineering.
• 5+ years of advanced AWS experience across EC2, VPC, IAM, EKS, RDS, Route53, S3, CloudWatch, CloudTrail, Config, and related services.
• Proven experience leading large-scale AWS migrations, including On-Prem AWS and shared-tenant Dedicated Host transitions.
• Deep hands-on expertise with AWS Dedicated Hosts, tenancy management, licensing considerations, and infrastructure lifecycle planning.
• Strong proficiency with Kubernetes, Terraform, cloud networking, and infrastructure automation.
• Excellent understanding of multi-account governance, security controls, and workload isolation.
• Strong communication and architectural leadership skills.

Equal Opportunity Employer

MACHINE LEARNING TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. MACHINE LEARNING TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will MACHINE LEARNING TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract