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Goodnotes

AI Engineering Lead

Posted Yesterday
Be an Early Applicant
In-Office or Remote
45 Locations
Senior level
In-Office or Remote
45 Locations
Senior level
Lead a team to develop and implement AI-driven productivity solutions, collaborating with stakeholders and promoting AI adoption throughout the organization.
The summary above was generated by AI

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
—Be visionary, strategic, and open to innovation
Build great things
—Work in service of our users, always improving and pushing higher
Operate like an owner
—Take responsibility with bold decision-making and bias for action
Win like a sports team
—Be trusting and collaborative while empowering others
Learn and grow fast
—Never stop learning and iterate fast
Share our passion
—Share ideas and practice enthusiasm and joy
Be user obsessed
—Empathetic, inquisitive, practical

About the team:

You will build and lead a small, dynamic, and cross-functional team tasked with identifying, building, and deploying AI-driven solutions to significantly enhance productivity across all departments at Goodnotes. Acting as an internal AI agency, your team will develop cutting-edge, practical tools using modern AI technologies as well as promote the adoption of AI across the entire Engineering organisation.

About the role:

This is the role for you, if you’re excited to work on the things listed below:

  • Lead and mentor a small engineering team dedicated to designing, developing, and deploying AI-powered productivity solutions internally.
  • Actively architect and implement AI applications leveraging LLMs, generative AI, NLP, predictive analytics, and process automation.
  • Collaborate closely with stakeholders from diverse business units (Product, Design, Customer Support, Marketing, etc.) to understand their needs and translate them into AI solutions.
  • Drive AI adoption across the broader engineering organization by sharing best practices, enabling internal teams, and embedding AI capabilities into existing products and workflows.
  • Define technical strategies, create clear roadmaps, and manage end-to-end delivery of impactful AI solutions.
  • Advocate best practices in AI software development, model training, testing, and deployment, ensuring reliability and scalability.
  • Build a culture of continuous learning, innovation, experimentation, and productivity enhancement through AI.
  • Track effectiveness of AI initiatives and continuously improve through iterative feedback loops.

The skills you will need to be successful in the above:

  • 7+ years experience in software engineering, with significant recent experience (at least 3 years) focused on AI/ML product development or implementation.
  • Proven experience developing, deploying, and maintaining AI solutions—ideally in enterprise or productivity contexts.
  • Demonstrated capability as a hands-on technical leader: still comfortable coding and prototyping, while effectively managing a small technical team.
  • Strong familiarity with current AI/ML frameworks and tools (e.g., PyTorch, TensorFlow, OpenAI API, LangChain, Hugging Face, vector databases, MCP, RAG, etc.).
  • Experience in productionizing AI solutions using cloud infrastructure (AWS preferred), and modern deployment techniques (e.g., Kubernetes, EKS, Terraform, ArgoCD).
  • Excellent communication, collaboration, and stakeholder management skills.
  • Strong problem-solving mindset, capable of creatively and pragmatically leveraging AI technology to address real business problems.
  • Deep curiosity and passion about leveraging AI to solve practical productivity problems.
  • A proactive, ownership-oriented mindset, comfortable with ambiguity and experimentation.
  • Desire to collaborate openly and foster an environment of continuous improvement, learning, and mentorship.

Even if you don’t meet all the criteria listed above, we would still love to hear from you! Goodnotes places a lot of value on learning and development and will support your growth if needed.
The interview process:

  • An introductory call with someone from our talent acquisition team. They want to hear more about your background, what you are looking for, and why you’d like to join Goodnotes
  • Live system design & Technical interview: two 1-hour live system design exercises about software and ML with some of our engineers. This is where you get to see what it would be like working at Goodnotes as well as the chance to ask any engineering questions you may have
  • Hiring Manager interview: A call with your hiring manager who is overseeing and managing entire engineering function in Goodnotes. This is the person who will be managing you day to day, working on your growth and development with you as well as support you throughout your career at Goodnotes.
  • Values interview – Meeting with members of the Goodnotes Team to answer behavioral questions related to our Values.
  • CEO interview: A call with our founding CEO.

What’s in it for you:

  • Meaningful equity in a profitable tech startup
  • Budget for things like noise-cancelling headphones, setting up your home office, personal development, professional training, and health & wellness
  • Sponsored visits to our Hong Kong or London office every 2 years
  • Company-wide annual offsite (we met in Lisbon in 2023, Bali in 2024, and Istanbul in 2025)
  • Flexible working hours and location
  • 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.

Top Skills

AI
Argocd
AWS
Eks
Generative Ai
Hugging Face
Kubernetes
Langchain
Llms
Ml
Nlp
Openai Api
Predictive Analytics
PyTorch
TensorFlow
Terraform

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