AI Infrastructure / Product Engineer
New
J
JobgetherAI legal technology
Remote; based in the United StatesFull-TimeMiddle
Salary180,000 - 260,000 USD per year
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Job Details
- Experience
- At least 3 years of professional experience
- Required Skills
- DockerPostgreSQLPythonRESTful APIs
Requirements
- Have at least 3 years of professional experience as a Software Engineer, Infrastructure Engineer, Product Engineer, or in a related engineering role building and deploying production systems.
- Have strong programming skills in Python and practical experience developing, maintaining, and deploying software applications.
- Have hands-on experience with cloud infrastructure and the deployment and operation of production software systems.
- Have experience building evaluation pipelines, benchmarks, or assessment frameworks for machine learning or AI-powered applications.
- Understand AI performance evaluation, including model accuracy, hallucination detection, retrieval quality, latency, and cost optimization.
- Have experience developing backend services, REST APIs, database integrations, and internal engineering tools.
- Be familiar with deployment pipelines, system monitoring, observability, and performance dashboards.
- Be able to turn experimental code, research prototypes, and loosely defined requirements into reliable, maintainable, user-friendly production solutions.
- Bring problem-solving and analytical skills to investigate complex technical challenges and deliver practical solutions.
- Collaborate effectively across engineering, AI research, and product teams.
Responsibilities
- Design, build, and maintain repeatable benchmarks and evaluation pipelines for AI and machine learning systems.
- Assess model accuracy, hallucination rates, retrieval quality, latency, and operational costs.
- Develop dashboards and monitoring tools for performance metrics, system improvements, and potential issues.
- Transform research prototypes and experimental AI capabilities into reliable, production-ready applications.
- Develop and improve AI-powered retrieval, document processing, drafting, and agent-based workflows.
- Integrate new models, techniques, and research findings into practical product features with AI research teams.
- Design, develop, and maintain backend services, APIs, and internal tools for AI testing, deployment, and product releases.
- Build and optimize databases, cloud infrastructure, and deployment pipelines for scalable AI applications.
- Implement monitoring, observability, and performance management solutions for system reliability and availability.
- Collaborate with AI researchers, product teams, and engineers on product capabilities, technical decisions, and engineering practices.
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