Applied AI Product Engineer

Orange Logic; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Orange Logic seeks a versatile engineer to turn promising AI ideas into production-ready apps, prototypes, and internal tools, often starting from open-ended problems. You will work across the stack, leveraging language models and coding agents as core development tools, and test solutions with users to determine value in complex content workflows.

Required: degree in CS or related field or equivalent experience; strong full-stack skills across frontend, backend, data and deployment; hands-on LM

Qualifications

• Strong full-stack skills across frontend, backend, data and deployment.
• Hands-on experience building apps with language models and model APIs.
• Portfolio of working products, prototypes, repositories or open-source work.

Responsibilities

• Investigate difficult or costly technical problems and build proof-of-concept solutions.
• Create end-to-end prototypes spanning UI, backend, data, integrations and deployment.
• Build language model systems using structured generation, tool use, retrieval, agents, model routing and evaluation.
• Combine models, APIs, databases, open-source software, and existing services to support content, metadata, search, and automation workflows.
• Put prototypes in front of users and stakeholders and adapt based on results.
• Explain system behavior and production considerations, balancing speed with security and reliability.

Skills

Full-stack development

Frontend development

Backend development

Data & deployment

Education

BS in Computer Science or related field

Tools

Model APIs

Retrieval/Agent workflows

Open-source tooling

Job description

Role overview

Turn promising AI ideas into working products, prototypes, and internal tools, often starting from an open-ended problem rather than a detailed specification. You’ll build across the stack, use language models and coding agents as core development tools, and test solutions with users to determine what can create meaningful value in complex content workflows.

Responsibilities

• Investigate difficult or costly technical problems and build proof-of-concept solutions that test what is possible.
• Create end-to-end prototypes and applications spanning user interfaces, backend services, data, integrations, and deployment.
• Build language model systems using methods such as structured generation, tool use, retrieval, agents, model routing, evaluation, and human review.
• Combine models, APIs, databases, open-source software, and existing services to support content, metadata, search, and automation workflows.
• Put prototypes in front of users and stakeholders, then adapt them based on observed results.
• Judge when rapid iteration is appropriate and when security, permissions, reliability, cost, or maintainability need more engineering; explain system behavior and production considerations.

Requirements

• A degree in computer science, engineering, or a related technical field, or equivalent practical experience shipping software.
• Strong full-stack skills and the ability to build across frontend, backend, data, and deployment.
• Hands-on experience building applications with commercial or open-source language models, including model APIs, context design, tool calling, or agent workflows.
• A portfolio of working products, prototypes, repositories, open-source work, or hackathon builds showing technical depth and execution.
• Ability to use AI-generated code effectively while independently reviewing architecture, debugging, and identifying security or quality risks.
• Resourcefulness with incomplete requirements, sound product judgment, and clear communication with technical and business partners.

Nice to have

• A habit of building side projects and experimenting independently is valued.