AI Engineer Secure AI
Micro1
Job Overview
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Job Description
About micro1
micro1 is the end-to-end human data infrastructure behind AGI. Our AI recruiter model is used by frontier AI labs and Fortune 10 companies to source and deploy top academic experts directly into training loops powering advanced AI systems.
Role Overview
The AI Engineer Secure AI will design, build, and ship secure, production-grade AI and agentic systems for high-assurance environments. You will work on systems from research prototypes to hardened deployments at the intersection of LLMs, agentic architectures, and secure cloud infrastructure.
- Design secure AI systems using Python and modern cloud platforms.
- Build multi-agent architectures including orchestration and prompt engineering.
- Develop and manage data pipelines, ETL, and metadata workflows.
- Integrate enterprise and government-grade LLM providers.
- Implement secure-by-default engineering practices across systems.
Responsibilities & Requirements
- Strong Python engineering with production system ownership.
- Hands-on experience with LLMs, LangChain/LangGraph, and prompt engineering.
- Experience in deploying systems on secure cloud infrastructure.
- Expertise in data pipelines, ETL processes, and structured data modeling.
- Proficiency in building REST APIs, SDKs, and CI/CD pipelines.
- Excellent communication skills for working with technical and non-technical teams.
Compensation & Benefits
The annual base salary ranges from $90,000 to $140,000 USD with additional equity and performance-based bonuses. A comprehensive benefits package includes full health-insurance premium reimbursement, paid time off, and more for our high-performing remote-first workforce.
Key skills/competency
- Python
- LLMs
- LangChain
- Cloud Security
- CI/CD
- ETL
- REST APIs
- Data Pipelines
- Agentic Systems
- Prompt Engineering
How to Get Hired at Micro1
- Customize your resume: Highlight Python and cloud experience.
- Emphasize security: Detail secure-by-default engineering practices.
- Prepare examples: Showcase AI system deployments.
- Practice interviews: Focus on technical and collaboration skills.
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