u/Available-Thing-7061

Hey folks,

I'm an experienced engineer - got years of experience in the industry and well versed with cloud technologies and distributed systems. However, my understanding of the whole AI/ML field is little to none, the most I have done is use GenAI/LLMs in order to supplement my work. I do not know what I do not know, and do not know where to even start. In fact, I even struggle to find the words to describe the problem below

With the industry shifting so fast, I have started seeing a lot of skills within jobs being around the ability to build backends for AI systems. Whether it is building data pipelines to feed into vector databases, scaling vector databases, embeddings (or whatever the heck that is), RAGs, MCPs, Agents, Agentic AI, etc

Does anyone have any suggestion on how experienced engineers can learn/prepare for the engineering part of AI systems ? For example, I would suspect system design interviews will start shifting to scaling vector databases (instead of just SQL/NoSQL), how to build scalable RAGs/MCPs/fine tuning, etc

Furthermore, are these considered 'ML System Design Interviews' ? Since I have started seeing that word being thrown around a lot. I do not intend to become a scientist that makes models, or understand the maths that make LLMs work. I want to learn the ENGINEERING side of it that can take existing models and deploy them as SCALABLE systems, along with scaling all its related surrounding infrastructure.

One of the ways I started learning System Design was by going through examples & problems in the book 'System Design Interview'. Is there any book or course that would cover the use case I have above ? I know they have new books such as 'The GenAI System Design Interview' and 'The ML System Design Interview', but I am not sure if thats for scientest/ML engineers or for regular engineers who are deploying these systems.

Please suggest !

Hey folks,

I'm an experienced engineer - got years of experience in the industry and well versed with cloud technologies and distributed systems. However, my understanding of the whole AI/ML field is little to none, the most I have done is use GenAI/LLMs in order to supplement my work. I do not know what I do not know, and do not know where to even start. In fact, I even struggle to find the words to describe the problem below

With the industry shifting so fast, I have started seeing a lot of skills within jobs being around the ability to build backends for AI systems. Whether it is building data pipelines to feed into vector databases, scaling vector databases, embeddings (or whatever the heck that is), RAGs, MCPs, Agents, Agentic AI, etc

Does anyone have any suggestion on how experienced engineers can learn/prepare for the engineering part of AI systems ? For example, I would suspect system design interviews will start shifting to scaling vector databases (instead of just SQL/NoSQL), how to build scalable RAGs/MCPs/fine tuning, etc

Furthermore, are these considered 'ML System Design Interviews' ? Since I have started seeing that word being thrown around a lot. I do not intend to become a scientist that makes models, or understand the maths that make LLMs work. I want to learn the ENGINEERING side of it that can take existing models and deploy them as SCALABLE systems, along with scaling all its related surrounding infrastructure.

One of the ways I started learning System Design was by going through examples & problems in the book 'System Design Interview'. Is there any book or course that would cover the use case I have above ? I know they have new books such as 'The GenAI System Design Interview' and 'The ML System Design Interview', but I am not sure if thats for scientest/ML engineers or for regular engineers who are deploying these systems.

Please suggest !

Hey folks,

I'm an experienced engineer - got years of experience in the industry and well versed with cloud technologies and distributed systems. However, my understanding of the whole AI/ML field is little to none, the most I have done is use GenAI/LLMs in order to supplement my work. I do not know what I do not know, and do not know where to even start. In fact, I even struggle to find the words to describe the problem below

With the industry shifting so fast, I have started seeing a lot of skills within jobs being around the ability to build backends for AI systems. Whether it is building data pipelines to feed into vector databases, scaling vector databases, embeddings (or whatever the heck that is), RAGs, MCPs, Agents, Agentic AI, etc

Does anyone have any suggestion on how experienced engineers can learn/prepare for the engineering part of AI systems ? For example, I would suspect system design interviews will start shifting to scaling vector databases (instead of just SQL/NoSQL), how to build scalable RAGs/MCPs/fine tuning, etc

Furthermore, are these considered 'ML System Design Interviews' ? Since I have started seeing that word being thrown around a lot. I do not intend to become a scientist that makes models, or understand the maths that make LLMs work. I want to learn the ENGINEERING side of it that can take existing models and deploy them as SCALABLE systems, along with scaling all its related surrounding infrastructure.

One of the ways I started learning System Design was by going through examples & problems in the book 'System Design Interview'. Is there any book or course that would cover the use case I have above ? I know they have new books such as 'The GenAI System Design Interview' and 'The ML System Design Interview', but I am not sure if thats for scientest/ML engineers or for regular engineers who are deploying these systems.

Please suggest !

Hey folks,

I'm an experienced engineer - got years of experience in the industry and well versed with cloud technologies and distributed systems. However, my understanding of the whole AI/ML field is little to none, the most I have done is use GenAI/LLMs in order to supplement my work. I do not know what I do not know, and do not know where to even start. In fact, I even struggle to find the words to describe the problem below

With the industry shifting so fast, I have started seeing a lot of skills within jobs being around the ability to build backends for AI systems. Whether it is building data pipelines to feed into vector databases, scaling vector databases, embeddings (or whatever the heck that is), RAGs, MCPs, Agents, Agentic AI, etc

Does anyone have any suggestion on how experienced engineers can learn/prepare for the engineering part of AI systems ? For example, I would suspect system design interviews will start shifting to scaling vector databases (instead of just SQL/NoSQL), how to build scalable RAGs/MCPs/fine tuning, etc

Furthermore, are these considered 'ML System Design Interviews' ? Since I have started seeing that word being thrown around a lot. I do not intend to become a scientist that makes models, or understand the maths that make LLMs work. I want to learn the ENGINEERING side of it that can take existing models and deploy them as SCALABLE systems, along with scaling all its related surrounding infrastructure.

One of the ways I started learning System Design was by going through examples & problems in the book 'System Design Interview'. Is there any book or course that would cover the use case I have above ? I know they have new books such as 'The GenAI System Design Interview' and 'The ML System Design Interview', but I am not sure if thats for scientest/ML engineers or for regular engineers who are deploying these systems.

Please suggest !

Hey everyone,

I am in tech and left a great job a early this year in order to join a startup.

It was a big pay cut, but I needed to go remote so I can live as a caregiver to my mom, she needs help as she is struggling with major health issues.

I thought it was a reliable job since one of my old coworkers who I did trust and have a great relationship with, was the one who reached out for the role. The start up had been operating for over a year, had a team that was slowly growing and a launch planned in late May.

Last week, I got informed that the start up is laying off the whole team, with only the two initial employees (one of which is my old coworker) who gets to stay.

I found out the start up was bought by a new owner who got oversold on what was developed so far by the startup. Thus, he decided last week this team is too expensive and its time to hire cheaper and more vulnerable employees that can be exploited for lower pay and higher hours (eg. newcomers to the country). Our team used to be a diverse set of folks who grew up here, the new folks coming in for interviews are all on a work permit or newly landed immigrants.

I do not want to incite any discussion on immigrant or hate against them, this is all mentioned only to understand what my options are for being laid off, whether I have the possibility of suing.

So here I am, laid off after 2 months of working in a new place - what are my options ? Am I supposed to get a severance ? What do I need to apply for EI ? Do I need some documentation from the employer that explicitly mentions that it was not performance related and due to business restructuring ?

Its my first time being in this situation, so please be kind !