Software Engineering Coach (GenAI + LLMs) (Hiring Immediately)

Role Summary

We’re looking for experienced lead engineers or equivalent to lead targeted micro-workshops for small groups of software engineers. The sessions last up to 90 minutes, take place remotely via our app, and based around high quality teaching material that we produce.

Your job is to bring expertise and enthusiasm for software engineering and ensure our learners leave with a deep understanding of the topic (understanding why , not just knowing what or how ), and the ability to apply new skills.

You can expect to be teaching senior as well as junior engineers, answering interesting questions tangential to our material, and helping learners to understand and improve the results they see when using LLMs. For this reason, we’ve found that the skill profile required is more similar to pairing or technical mentoring than it is to typical classroom teaching.

About Skiller Whale

Skiller Whale changes what tech teams are capable of through live sessions led by subject-matter experts.

Developers attend a 60-90 minute session every week or two, learning something new through challenging exercises with an expert leading the session to explain the topic and answer difficult questions. Learners love us (they give us an average rating of 4.8 / 5) and we have a measurable impact on the teams we work with.

Our learners say:

| The real-time feedback loop of learning something, putting it into practice and getting insight beyond 'it works' beats any other learning experience I've had by miles

| “I loved that I could ask any questions at all, and learned new things even in a technology I’ve been using for 15 years!”

| “The biggest pro of Skiller Whale is the quality of the coaches. I really appreciate the deep knowledge they had both on the internals of Python, and how to architect systems”

What We're Looking For

We'd love for you to apply if you enjoy building the skills and understanding of others, and have experience with most (at least 4) of the following:

• Explaining basic machine learning concepts to others.
• Some knowledge of LLM internals, e.g. transformer building blocks (at least enough to underpin deeper understanding of their behaviour)
• Prompt engineering
• Agentic AI & using IDE integrations with AI agents
• Coding with LLMs, e.g. setting up Cursor/Copilot configs, and writing prompts for coding/debugging
• Integrating/Pipelining with LLMs, e.g. langchain
• Customising LLM tools, e.g. fine tuning LLMs, using RAG systems

You’ll need to have significant expertise and experience in a real-world setting, be able to give nuanced answers to difficult questions, and explain advanced concepts clearly and succinctly.

An outline of the first modules of this curriculum can be found here:

More Details

Working Hours

Most of our coaches lead between 1 and 4 sessions per week (1.5 - 6 hours), with Skiller Whale making up part of a portfolio career, or adding variety to their main employment, consulting or fractional roles. We typically book regular weekly 90 minute time-slots for these sessions, based around your availability.

The Platform

All our teaching is done through the Skiller Whale platform, which includes video conferencing and other tooling designed to make teaching as slick as possible. High quality written content and exercises are provided by Skiller Whale, so you shouldn’t need to do significant preparation before a session (we assume ½ - 1 hour to get familiar with the material, and we pay for preparation the first time a module is taught).

Accommodations

Should you require any accommodations during the interview process, please reach out to Dave Millican ( [email protected] ) to let him know. We’re always happy to help and will do everything we can to accommodate you.

Requirements

We want to be seen as intelligent, playful learners. Our customers need to trust us to teach their engineers how they should be building software and working effectively in the real world. For our coaches, that means you need to demonstrate:

Knowledge & Understanding

You should come across (legitimately) as an expert, able to expand beyond the provided material when appropriate. E.g: examples from your experience in different settings; what you’ve found works we]]> <