So who should we hire now?

This is a question we are constantly asking ourselves as our understanding of the specific challenges of delivering Gen AI projects for Enterprise clients develops. We believe it has changed the hiring candidate profile at Brightbeam quite a lot! In light of the rapid advancements in generative AI, the landscape of recruiting a robust engineering team has undergone significant changes. We’ve built large engineering teams and organisations over the last twenty-five years, but we’re learning a lot, and we wanted to share the challenges and shifts in hiring profiles necessary to build a competent team in this new era.

Generative AI has accelerated development processes, allowing individual engineers to:

• Efficiently write and improve user stories
• Quickly write unit tests
• Generate code snippets and stubs when development starts
• Rewrite and refactor code
• Analyse errors and bugs
• Develop boilerplate and utility code
• Create integration tests and harnesses

This efficiency and speed means that tasks previously requiring five developers can now be managed by one or two.

Enterprises have a reputation for having large teams—probably far larger than required. We have a very high bar for what we consider quality software, and the latest tools allow us to have small teams.

Previously, a team of five developers might include:

1. A front-end developer with expertise in user interfaces
2. A back-end developer with architectural knowledge
3. A designer
4. A cloud and infrastructure specialist
5. A communications and project management expert

Each member brought specialised skills, contributing to a well-rounded project team likely to deliver a quality outcome.

Testing and quality may or may not be embedded in the engineering teams, but often has many people involved in the process.

With the incorporation of Gen AI accelerating elements, we are delivering more with smaller teams, and the ideal candidate’s profile has evolved. Now, a single developer must possess:

• Proficiency in software development
• Back-end development skills
• Knowledge of front-end design
• Cloud deployment expertise
• Understanding of data engineering
• Skills in prompt engineering & a basic understanding of LLMs
• Testing and quality automation

This shift demands a broader skill set within individual team members.

We also find ourselves delivering software to clients unfamiliar with the development process. This increases the need for:

• Enhanced communication skills
• Ability to educate and upskill stakeholders

Our hiring profiles now focus on individuals with broad experiences or those who are interested in developing broadly:

• Extensive experience across various domains
• Background in infrastructure, front-end development, project management, and Agile frameworks.
• Proficiency in software engineering and production-grade systems

Experienced professionals who have navigated different roles are better suited to excel in this new environment.

But we are open to both experienced and inexperienced profiles.

The evolution of the hiring profile also emphasises distinct criteria for Senior and Junior Engineers:

Senior Engineers:

• High bar for engineering quality, including problem decomposition, architectural choices, performance, maintainability, and adherence to good practices and principles.
• Ability to create an environment that helps new team members become productive quickly and encourages a culture of continuous learning.
• Can help people become great at their craft whilst maintaining their own skills and capabilities.

Newcomers to the industry, native to generative AI, seem to adapt quickly. However, mid-level professionals with limited experience across multiple pillars are definitely struggling. This creates a unique dynamic where continuous learning and professional development are crucial. When we think about more junior team members, we are looking for people with:

• Curiosity, attention to detail, and willingness to learn and explore.
• Openness to new experiences and adaptability to evolving technologies and methodologies.
• Willing to try by doing and motivated to find answers using GenAI and other resources.
• Able to contribute ideas and give feedback.

The definition of a “good developer” is evolving. We are adjusting our hiring profiles to match this new reality and are beginning to find candidates who meet our comprehensive requirements. This transition is both challenging and exciting as we build a team capable of thriving in the age of generative AI. In the 90’s and early 00’s a great programmer was great at writing lines of code, after 2010 the capability to utilise Open Source and Cloud services became just a important. With the advent of Gen AI it looks like software engineering will be the first industry to be truly disrupted and we will see the rise of the multidisciplinary expert engineer. If this sounds like you then we’d love to speak with you!!!!