Sr. Technical Architect

Sr. Technical Architect

https://jobs.micro1.ai/post/cf633740-7783-442e-881b-bbad6912770b?referralCode=1761f2a1-0970-4c4f-a273-a1b557d5ad9f&utm_source=referral&utm_medium=share&utm_campaign=job_referral

Role Type

Contractor

Location

Remote

In this role, you'll apply your platform engineering expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world engineering input. No prior experience in AI is required-your domain knowledge and hands-on production experience are what matter.

As an expert, you will create Reinforcement Learning Environments that test an AI model's ability to design, deploy, troubleshoot, secure, scale, and recover production-grade cloud infrastructure. You will develop realistic scenarios involving distributed systems, networking, IAM, queues, durable storage, observability, rolling deployments, and disaster recovery, then build reproducible environments, deterministic validation tests, golden reference solutions, and intentionally defective variants.

Responsibilities

Create realistic cloud infrastructure tasks involving distributed systems, networking, security, scalability, and reliability.

Build reproducible, containerized environments with valid reference solutions and intentionally defective variants.

Define measurable requirements across infrastructure configuration, deployed topology, and runtime behavior.

Develop deterministic integration, load, security, failure-injection, deployment, and recovery tests.

Debug environments, document technical decisions, and review tasks created by other experts.

Required Skills and Qualifications

Senior-level technical architecture, cloud infrastructure, platform engineering, DevOps, systems engineering, or SRE experience, including personal ownership of a production platform.

Strong knowledge of distributed systems, scalable APIs, queues, autoscaling, durable storage, and partial-failure scenarios.

Practical experience with IAM, private networking, least-privilege access, and service-to-service security.

Experience with observability, measurable SLOs, rolling deployments, rollback strategies, and disaster recovery.

Ability to write infrastructure automation or testing tools and debug containerized environments using a relevant programming language.

Preferred Qualifications

Experience with Terraform or OpenTofu.

Experience with AWS, Azure, GCP, Kubernetes, or multi-cloud infrastructure.

Experience building internal developer platforms, edge infrastructure, or shared platform services.

Experience with chaos engineering, fault injection, local cloud emulators, or resilience testing.

Experience creating technical evaluations, automated grading systems, or AI environments is helpful but not required.

Process

Apply to the role, filling out the screening questions

Complete AI interview (aprox. 30 minutes), reviewed by recruiters)

Hiring Manager review

Compensation Structure

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert's experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.