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.
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
“This role is perfect for an engineering leader who is passionate about using AI to supercharge developer productivity and happiness. You will own both (1) building an internal “AI agency” that delivers high-impact AI solutions across all functions, and (2) fundamentally improving how our 200+ engineers build software—tooling, workflows, CI/CD, code generation/review, local dev environments, knowledge retrieval, and engineering intelligence.
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.
- Lead the transformation of our engineering practices by applying AI to developer tooling and workflows (e.g., AI-assisted code review, test generation, documentation, debugging, onboarding ramps, engineering metrics/dashboards, and internal knowledge retrieval).
- Own the Developer Experience roadmap in close partnership with platform and toolchain teams; measure and improve key metrics such as build times, deployment frequency, PR cycle time, and engineer satisfaction.
- 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:
- 8+ years in software engineering, with at least 3–4 recent years in a DevEx/platform/infrastructure leadership role at a high-growth tech company.
- Proven track record of leading AI-driven developer productivity transformations (examples: AI code assistants, automated testing frameworks, RAG-based internal search, engineering copilots, or similar initiatives that delivered measurable velocity/quality gains)
- Demonstrated experience building and deploying production AI systems—ideally internal tools that engineers love using every day.
- Hands-on technical leader: still writes and reviews code regularly, prototypes quickly, and can dive deep when needed.
- Deep expertise with modern AI/ML ecosystems (PyTorch, LangChain, OpenAI/Anthropic/Cohere APIs, vector DBs, RAG, agent frameworks, evaluation tooling) and developer platforms (GitHub Actions, Buildkite/CircleCI, Kubernetes/EKS, observability stacks, Backstage or similar).
- Strong experience productionizing AI on AWS (EKS, Bedrock, SageMaker, RDS/Vector stores, Terraform/Infra-as-Code).
- Exceptional stakeholder management: able to translate vague “this is slow” complaints from engineers or other departments into concrete, high-ROI AI solutions.
- Passion for both (a) shipping delightful internal products and (b) removing friction from the daily life of engineers.
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 (across Europe and Asia time zones)
- 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.
