Software Engineer
Job Description
Job Title: Software Engineering
Job Type: Contractor (10-15 hours per week)
Location: Remote
Required Skills: Javascript, Typescript, Java, C#, C++, Golang, Ruby
Job Summary:
We are looking for experienced software engineers to help train and evaluate next-generation AI systems through real-world software engineering tasks. This role is best suited for developers who can reason through unfamiliar codebases, explain engineering decisions clearly, and solve practical backend, full-stack, systems, or infrastructure-related problems.
A Cybersecurity/SecOps background or exposure is highly preferred
No prior AI experience is required. What matters most is strong software engineering judgment, clean technical communication, and the ability to evaluate code, architecture, tradeoffs, and implementation quality.
Key Responsibilities:
Work on challenging software engineering tasks across backend, full-stack, infrastructure, and systems-related projects.
Review, debug, improve, and explain code across different technical environments.
Design or evaluate practical solutions involving APIs, databases, services, integrations, testing, and deployment workflows.
Identify tradeoffs around scalability, maintainability, performance, reliability, security, and developer experience.
Communicate technical reasoning clearly in writing, including why a solution works and what alternatives were considered.
Collaborate with the customer’s team on technical reviews, implementation decisions, and problem-solving exercises.
Adapt quickly to new codebases, frameworks, and technical requirements.
Required Skills and Qualifications:
3+ years of hands-on software engineering experience.
Strong experience in at least one backend or full-stack engineering environment, such as Python, JavaScript/TypeScript, Node.js, Java, C++, Go or Ruby
Experience building, maintaining, or reviewing production-level applications, APIs, services, databases, or integrations.
Strong understanding of software engineering fundamentals, including debugging, testing, code quality, architecture, and technical tradeoffs.
Ability to explain complex engineering decisions clearly and objectively.
Comfortable reading and reasoning through unfamiliar code or technical requirements
Preferred Qualifications:
Experience with cloud environments such as AWS, GCP, or Azure.
Experience with CI/CD pipelines, DevOps workflows, containers, monitoring, or production operations.
Experience with frontend frameworks such as React, Next.js, Angular, Vue, or React Native.
Open-source contributions, public GitHub work, technical writing, or strong examples of past engineering work.
Experience mentoring engineers, reviewing code, or making architecture decisions.
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.

