Engineering manager with a strong technical foundation in distributed systems and cloud-native architecture.
I scale teams, connect business context to technical execution, and prefer clear systems over noisy process. This site is intentionally simple: key links first, a concise record of experience, and the opinions I am shaping around software development and AI usage.
From implementation and architecture to engineering management.
Being able to focus on project delivery and use project context to grow the team.
From greenfield projects to legacy modernization at global scale.
A practical overview of the tools and platforms I use to design, build, and deliver software systems.
Building the back-end is one of the areas I enjoy the most. Defining a clear ubiquitous language and bounded contexts and developing a sense of ownership from the delivery team are essential to me. Developing a strong structure for the system to be easily adaptable to change and growth is something I prioritize from the start.
When it comes to frontend, my priorities go beyond 'creating a responsive layout'. Creating a strong project structure, processes and tests using tools like Playwright and Maestro are often essential to ensure maintainability and scalability.
In an age of rapid development due to AI, creating a structure where code can be easily and safely deployed to production is more important than ever. Providing application security guardrails and having strong observability are essential skills.
Software gets built by people, for people. The tools that we use and the processes keep changing, but the fundamentals are always there. My leadership style focuses on creating ownership within the delivery teams and providing them with the right setup to do their best work. Whether by providing technical foundations, removing blockers, or navigating complex business logic.
I work best in environments where the team has autonomy to make decisions and my voice can be one of many in the room. Providing strong business insights and bridging the gap between tech, business and customers is something I excel at.
It does not matter the domain, creating a strong connection between the delivery team and the product is what allows them to make good technical decisions and have ownership of the work.
Having processes in place for testing, security, observability, automations and clear architecture is what allows teams to move fast without losing quality or sleep.
Creating an environment where the tech team in a company is pushed to improve themselves is essential for a Tech company.
Being one of the main topics, I could not skip sharing my thoughts.
Agent workflows can outpace non-assisted workflows. It is our responsibility to find ways to direct this high velocity towards actually good software being delivered, matching the product goals.
Having these items in place is essential if the code output is higher.
The AI can be a great assistant, but it needs the correct context to make good decisions. Providing the right information about the product, the users, and the business goals is essential to get good output.
Utilizing the correct models, tools, agent and sub-agent architectures, and hosting. These are fundamental items to use AI in a responsible manner.
The tools and environment I use daily to design, develop, and deliver software.
These tools provide me a rapid development loop, allowing me to switch between projects and context with ease.
Creating a structured harness for the agents to operate saves time and allows for more async development.
Being able to use a different range of models for specialized situations is essential to get good output and optimize costs.
Having a strong MCP setup can sometimes be beneficial to explore scenarios faster.