Senior Backend Engineer

📍remote
🕒Full-time
💰$50 – $100/hr
📅Posted August 6, 2026

Job Description

Role Title: Senior Backend Engineer

Role Type: Contractor (20 hrs perweek)

Location: Remote

micro1 is engaging Senior Backend Engineers to participate in an advanced project for a customer, focused on creating sophisticated Reinforcement Learning Environments for AI model training and evaluation. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

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.

Scope of Work

  1. Design, develop, and implement realistic cloud infrastructure environments to evaluate AI model proficiency in systems design, deployment, and troubleshooting.

  2. Create detailed and reproducible scenarios involving distributed systems, networking, Identity and Access Management (IAM), message queues, persistent storage, observability, rolling deployments, and disaster recovery.

  3. Develop deterministic validation tests and golden reference solutions to ensure the reliability and accuracy of reinforcement learning environments.

  4. Produce intentionally defective variants and failure scenarios to rigorously test AI model responses and recovery strategies.

  5. Document the architecture, edge cases, and operational flows for all developed environments, ensuring clarity and reproducibility for future use.

  6. Collaborate with technical leads and project participants to iteratively refine environment specifications and acceptance criteria.

  7. Apply DevOps and infrastructure automation practices to deliver scalable, secure, and maintainable solutions for cloud-based systems evaluation.

Preferred Qualifications

  1. Proven expertise with backend programming languages, such as C++, Python, Rust, GoLang, JAVA, or JavaScript.

  2. Strong practical experience with DevOps, cloud infrastructure, CI/CD pipelines, and automation tools.

  3. Demonstrated ability to architect, scale, and secure distributed systems in production-grade environments.

  4. Deep understanding of networking, IAM, queues, durable storage, and disaster recovery concepts.

Process:

  1. Apply to the role, filling out the screening questions

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

  3. 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.

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About Micro1

Micro1 is building the essential infrastructure for the next generation of artificial intelligence, moving beyond the limitations of static datasets to create a dynamic ecosystem where models truly learn to think and act. At its core, the company understands that the path to frontier intelligence isn't paved with synthetic data alone; it requires the nuance, judgment, and contextual awareness that only expert human guidance can provide. By positioning itself at the intersection of human expertise and advanced reinforcement learning, Micro1 is tackling the hardest problem in AI today: teaching models not just to answer questions, but to reason through complexity and take meaningful actions in unpredictable, real-world environments.

This mission comes to life through Realm, Micro1's flagship training environment. Realm functions as a high-fidelity simulation ground where AI agents are immersed in scenarios that closely mirror the messiness of actual human workflows. Rather than relying on abstract benchmarks, Realm forces models to engage in agentic actions, multi-step decisions, digital navigation, coding, and problem-solving that require genuine comprehension. It is within these realistic sandboxes that world-class human data is generated, creating a continuous feedback loop where expert annotators observe, correct, and guide model behavior. This process does more than just fine-tune outputs; it fundamentally elevates a model's underlying reasoning architecture, ensuring that the intelligence developed in training holds up when deployed into the wild.

But training is only half the equation. Micro1 recognizes that the true test of an AI system lies in its production performance, which is where Cortex enters the picture. Cortex is a contextual evaluation platform designed to move beyond superficial accuracy metrics and provide a granular, real-time view of how agents behave in live settings. It doesn't just flag errors; it surfaces the underlying context behind failures, revealing why an agent struggled with a particular user intent or environmental variable. This insight is invaluable for engineering teams, as it transforms evaluation from a passive checkpoint into an active improvement tool. With Cortex, companies can catch degradation early, understand the nuances of edge cases, and feed those learnings directly back into Realm for retraining, creating a virtuous cycle of continuous advancement.

Ultimately, Micro1 is not merely a data lab or an evaluation tool it is a comprehensive intelligence engine that connects the entire lifecycle of model development. From the expert human feedback that sharpens raw capability, to the realistic RL environments that forge robust agentic behavior, to the contextual oversight that ensures reliability in production, Micro1 provides the integrated foundation that AI labs and enterprises desperately need. As the industry races toward truly autonomous systems, Micro1 stands as the critical bridge between laboratory breakthroughs and dependable, real-world impact, ensuring that frontier models do not just perform well on paper, but deliver genuine value in the complex, dynamic world they are meant to serve.