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Yes, I am an hands on engineering manager

- It all depends on the task and how open ended it is plus which engineers I have eg

If task is open ended all my senior, staff engineers are busy, I will get  clarity on prioritisation eg whats the priority based on eg what benefit it will have? more revenue, customer satisfaction, decreased tech debt etc. Accordingly I will prioritise.

If it requires immediate prioritisation and I cant get my senior folks in this, but I see that this problem can challenge a junior dev, I will try to create clarity for them and assign it to them post clarity.

If none can be done, I will negotiate with senior leadership on prioritisation and compare with all the other items on my teams plate. I will also check if somebody wants to challenge themselves and volunteer for this problem.

I would like to talk about situation. When I was an engineering  manager at digital commerce platform org at Amazon, I was handling close to 11 services, and 

as part of the Rolling Stone initiative where Amazon was trying to move all its services away from Oracle, I had four services that I was trying to migrate from Oracle to the databases hosted on Azure. All my fellow colleagues who were owning services of DCP were doing similar exercise. One of the colleague who was owning digital redemption service had to go on maternity leave, and then couple of engineers earmarked to do this migration for digital redemption service wwere transition out of the organization. That is when I offered to help with the migration of the service. 

So I now had 5 services with competing  priorities where I 

had to manage very tight schedule of service migrations. Planning a very ruthless prioritization, figuring out an optimal execution path of a completely unknown service, interacting with the service upstream clients whom i had not worked with prior, working with an amalgam of My team members and the service owner team members were few of the ambiguous paths I navigated to help do on time migration completion of the   service owned by my collegues.

At my previous role, I was leading a fraud detection AI model deployment for a financial services client. The model aimed to reduce fraudulent transactions by 25% while maintaining a low false positive rate.

I was confident in the model’s performance in the test environment, but when we deployed it in production, we noticed an unexpected spike in false positives. Transactions flagged as fraudulent were legitimate, causing disruptions for customers and increasing manual review work. To resolve this, I:

1. Investigated the issue by comparing training and production data.

2. Identified data drift—the model was trained on historical data, but recent transaction patterns had changed.

3. Worked with data engineers to implement real-time data monitoring.

4. Retrained the model with up-to-date data and adjusted hyperparameters to improve generalization.

This fix reduced false positives by 25%, improved fraud detection accuracy, and ultimately saved $500M in operational savings across multiple initiatives. This experience taught me the importance of continuous model monitoring and proactively accounting for data drift. Now, I always incorporate data validation pipelines and feedback loops into AI deployments to prevent similar issues.

I was working on a high stake project with very high visibility from my senior management.

Me and my manager were thinking of can we leverage the quality of the development using help from QA team. He wanted to keep the QA team separate. His point of view was that a separate team would keep clear focus for the team and they would focus on finding more customer facing bugs. I thought that we should have QA embedded in the scrum team as that would help in easier collaboration and quicker bug fixes plus this is a more efficient way. Though I understood his point of view I always believed that in QA embedded inside the scrum team. I went back had a thought to measure the merits and demerits of the proposals. I put down in a slide the merits and demerits of each. Merit from having a separate team, clear focus and better filtering of quality, demerits less collaboration with development team. I then proposed that the QA engineers attend the calls of dev teams but keep a separate QA board for their tasks. This will give clarity of what bugs they find, what test scenarios they create and finally the metrics to measure the bugs reported per development. My boss and I both agreed as it solved the problems of each proposals