This page contains a list of roles in the tech industry that I am familiar with.

• Level: This is a number which represents the level of seniority associated with your role or position, e.g., L2 (I), L3 (II), L4 (III)
• Band: A band refers to a group of levels of a role or position that map out a stage of a career in terms of YOE, e.g., Entry-Level, Junior, Mid, Senior.
• Googleyness: Attributes like enjoying fun (who doesn't), a certain dose of intellectual humility (it's hard to learn if you can't admit that you might be wrong), a strong measure of conscientiousness (we want owners, not employees), comfort with ambiguity (we don't know how our business will evolve, and navigating Google internally requires dealing with a lot of ambiguity), and evidence that you've taken some courageous or interesting paths in your life. "I accomplished X, relative to Y, by doing Z.”
• Individual Contributor: This is a software engineering career track that focusses on roles where technical skills and coding comprise a majority of the work.
  • Software Engineer I (L2): New graduates and interns at entry-level.
  • Software Engineer II (L3): Junior SWEs with 0-3 YOE.
  • Software Engineer III (L4): Mid SWEs with 3+ YOE.
  • Senior Software Engineer (L5): Senior SWEs with 5+ YOE.
  • Staff Software Engineer (L6): Top 10% of SWEs that manage engineering teams from a technical standpoint with 10+ YOE.
  • Senior Staff Software Engineer (L7): Duties of L6 but significant work required to move to L7 again with 10+ YOE.
  • Principal Engineer (L8): Play a pivotal role in implementing technical approaches for large-scale developments while coordinating huge teams of software engineers with 10+ YOE.
  • Distinguished Engineer (L9): Responsible for creating effective technical strategies.
  • Engineering Fellow (L10): Known as Vice Presidents (VPs), who lead thousands of engineers in leading technical contributions. It is an esteemed status secured for the world's leading software engineering professionals.
• Engineering Management: This is a software engineering career track that focusses on roles where soft skills and management comprise a majority of the work.
  • Software Engineering Manager I (L5): Manage team of 5-10 SWEs.
  • Software Engineering Manager II (L6): Manage team of up to 20 SWEs.
  • Software Engineering Manager III (L7): Manage team of 20-40 SWEs.
  • Director (L8): Shifting into an executive role within the organisation.
  • Senior Director (L9): Primarily a privileged position, with formal statements regarding the promotion only made within the company.
  • Vice President (L10): Lead hundreds and thousands of employees and are accountable to board of directors.
• Software Engineer (SWE): SWE is about shipping and maintaining code according to deadlines. Typically a CS or SWE undergraduate degree is a required qualification for this role.
• Frontend Engineer:
• Backend Engineer:
• Full-stack Engineer:
• Solutions Architect:
• Site Reliability Engineer (SRE): SRE is a combination of SysAdmin and SWE, though most SREs lean towards one or the other, it is expected that SREs have some YOE in both. SRE is about solving efficiency, scalability and reliability problems of software systems through making effective use of automation and tooling. Invented by Google, the role can be described as “Keeping Google up and running”.
• DevOps Engineer:
• Research Engineer: This is a role within an AI lab that typically requires a masters or PhD qualification to be considered. Research Engineers collaborate with SWEs and Research Scientists to solve the more practical engineering aspects of research problems in AI. They contribute in part to writing academic papers but that is not their main objective which is actually to enable Research Scientists by unblocking their technical difficulties so they can focus on producing research results in the form of published academic papers.
• Research Scientist: This is a role within an AI lab that typically requires a PhD qualification to be considered. Research Scientists collaborate with SWEs and Research Engineers to solve the most current research problems in AI. Their main objective is to produce research results in the form of published academic papers.
• Data Scientist: Data Science is at the intersection of Stats, CS and Domain Knowledge. The role of a data scientist within an organisation is to tell stories with data, capturing the narratives relevant to their clients and stakeholders whilst extracting valuable insights from those stories which can then be factored into the decision-making process and acted upon. Typically a data scientist requires at least a masters qualification in Stats, DS, CS or Math or a related numerate discipline to be considered.
• Data Engineer: