Signal AI is scaling both our customer base and engineering team as we expand our offering into new markets. The increased scale we’re now operating at naturally brings a greater need for clarity regarding how software engineer career progression works at Signal AI. Additionally, presenting us with the opportunity to review what we should expect from our engineering team.
As such, this is the second iteration of our software engineering progression framework. The first iteration of this framework worked well to distinguish a limited set of roles when we were a smaller team, and we expect this version to work well for our next stage of growth. It will continue to be under review and undergo further iterations as we continue to evolve as a business.
How we’ve built this framework
This framework is built around three key pillars that we believe to be strong indicators of the overall value a software engineer brings to our business. Those pillars are Behavioural Approach, Technical Mastery, and Influential Impact, and they are each outlined below:
Behavioural Approach
Our values are central to how we all experience working at Signal AI and to the company we want to build. How you generate impact and exert influence is as important as the results you achieve, and is what separates long term success from short term results achieved with an unacceptable cost.
Everyone at Signal AI is expected to work in line with our values. Still, the extent in which you can demonstrate these will vary with seniority.
Technical Mastery
Our success comes from putting working software into the hands of our customers. An engineer’s level of technical mastery determines the extent to which they are able to discover, design, build, deploy and support our software to meet the needs of customers today and into the future.
In measuring mastery, we aim to measure an engineer’s ability to balance discovery work and predictable delivery, repeatedly make sound technical choices by anticipating what might change, skillfully weigh trade-offs and ensure the right levels of quality, scalability, reliability and observability in a complex and changing landscape.
Influential Impact
We work in cross-functional teams where everyone needs to be aligned and work together to be effective. As an engineer’s career progresses it is expected that their level of influence will gradually increase. The wider an engineer’s sphere of influence the more that they affect the impact that other engineers are able to achieve, and as such this is a key measure of engineering seniority at Signal AI.
Influential impact measures ability and capacity to effect the status quo in relation to furthering our mission to change the way businesses make decisions through their own personal contributions of building software, designing architectures, automating (or eliminating) repeated work, sharing knowledge, coaching others and much more.
Using this framework
This framework can be used to help shape conversations between an engineer and their manager. It’s meant as a guide both to gauge the level at which an engineer is consistently performing and to explore areas for further development.
It should be used only as a guide and not as an exhaustive list of boxes to be ticked. There is significant variety in what different teams need to achieve and how they generate impact, so trying to capture everything would be counterproductive therefore hindering our ability to get the best from everyone by developing people according to their natural strengths and the needs of the business.
Finally, levels as presented in this framework are cumulative so each one builds upon the skills and behaviours from the levels that come before it. As such, levels should not be considered in isolation.
Scope is an additional measure for different levels of seniority together with the ambiguous nature of their work. As Signal AI grows, so should the reach or impact of the problems we encounter as engineers.
Our Levels
The levels in Signal AI’s Software Engineering career path are outlined below: