AI Solutions Engineer

AI Solutions Engineer at Goodnotes

At Goodnotes, we believe that every individual holds untapped potential waiting to be unleashed. By reimagining the way we interact with information, we’re merging human creativity with the breakthrough capabilities of AI. Our renewed vision and mission drive us to create the best medium for human and AI collaboration, empowering users to explore new dimensions of productivity, creativity, and learning. Join us on this journey as we transform digital note-taking into an inspiring and innovative experience.

Our Values

• Dream big
• Build great things
• Operate like an owner
• Win like a sports team
• Learn and grow fast
• Share our passion
• Be user obsessed

About The Team

You’ll be part of a small, cross-functional, and dynamic team focused on identifying and building AI-powered solutions that boost productivity across all departments at Goodnotes. The team functions like an internal AI agency—experimenting with modern AI technologies, building impactful internal tools, and driving AI adoption across the engineering organization.

About The Role

We’re looking for a mid-level Software Developer Productivity Engineer or Developer Experience Engineer with a passion for AI and practical problem-solving. You’ll contribute directly to the design, development, and deployment of AI-powered solutions that improve productivity across the company. This is an individual contributor role where you'll be deeply involved in coding, prototyping, and learning on the job.

This is the role for you if you're excited to:

• Build and deploy AI-driven internal tools using technologies like large language models (LLMs), retrieval-augmented generation (RAG), AI agents and orchestration frameworks, vector databases, and automation pipelines
• Collaborate with teammates and cross-functional stakeholders (e.g. Product, Design, Marketing) to understand real business needs and translate them into technical solutions
• Stay hands-on with modern AI/ML tools (e.g., AI agents, MCP, A2A, AI SDKs, vector databases, etc.)
• Contribute to experiments and proof-of-concept projects to explore new opportunities for AI in the workplace
• Use coding agents to generate clean, scalable, and maintainable code to bring AI prototypes into production
• Learn continuously and share new insights and best practices with your team
• Help integrate AI into internal workflows and assist other teams in adopting AI-powered features

You’ll thrive in this role if you have:

• 3–5 years of experience in software engineering, with some hands-on exposure to AI/ML projects
• Familiarity with AI/ML tools and platforms (e.g., AI APIs and SDKs, LiteLLM, n8n, OpenWebUI, etc.)
• Experience developing backend services and integrating APIs
• Comfort with deploying cloud-based solutions (AWS preferred) and an understanding of modern DevOps practices
• A pragmatic and user-focused mindset—eager to solve real business problems with practical AI tools
• Strong communication and collaboration skills
• A willingness to experiment, learn, and improve through feedback and iteration

Even if you don’t meet all the criteria listed above, we’d still love to hear from you!

Goodnotes values learning and development and will support your growth if needed.

Interview Process

• Introductory Call
• Hackerrank Challenge
• Code Review & System Design Interviews
• Hiring Manager Interview
• Values Interview
• AI Literacy

What’s in it for you

• Meaningful equity in a profitable tech startup
• Budget for home office, professional development, wellness, and more
• Sponsored visits to our Hong Kong or London offices every 2 years
• Annual company offsites (Lisbon in 2023, Bali in 2024, and Istanbul in 2025!)
• Flexible working hours and location
• Comprehensive medical insurance for you and your dependents

Note: Employment is contingent upon successful completion of background checks, including verification of employment, education, and criminal records.

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Key skills/competency

• AI/ML Solutions Development
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Vector Databases
• Backend Services
• Cloud Deployment (AWS)
• DevOps Practices
• API Integration
• Prototyping & Experimentation
• Software Engineering