Gen-AI Engineer

About the job

Description

Equal Experts is an innovative consultancy specialising in the delivery of custom software solutions for blue-chip enterprise and public sector clients across a range of industry sectors. We work on important projects for our clients, deliver market-leading propositions across the digital, online and mobile channels, and are recognised for our leadership in the application of agile and lean delivery methods to assure delivery.

We’re seeking backend engineers with proven senior-level experience to join Equal Experts.

You should have extensive experience delivering software on commercial projects backed up by extensive knowledge of agile practices such as TDD, pair programming and CI/CD to name a few. As well as an interest in working with latest ways with AI in the Software lifecycle.

A growth-based, learning mindset is a must coupled with a passion for technology. This role involves working in teams that use modern agile technical practices - including continuous integration and deployment and fast feedback loops - to deliver timely and pragmatic solutions, as well as helping others to do their jobs in a more effective way.

Responsibilities

Solution Prototyping & Testing: Rapidly test various models and approaches to determine the best fit for the project without extensive over-investment. Stay updated on LLM advancements (e.g., GPT-3.5 to GPT-4).

Prompt Engineering: Write, test, and refine prompts, including creating effective prompt chains and managing prompt versions for optimal results.

Model & Prompt Evaluation: Analyze model and prompt performance to ensure reliability. Develop robust testing methodologies, incorporating training and test sets for thorough evaluation.

Performance Monitoring: Build pipelines to monitor model responses and track performance metrics in production for ongoing optimization.

RAG Architecture Implementation: Design and maintain retrieval-augmented generation (RAG) architectures. Work with data pipelines, vector databases, and search algorithms. Manage document chunking and embedding selection for optimal context window usage.

Data Extraction: Extract data from various sources (e.g., PDF files) as part of the RAG process.

Software Development Best Practices: Employ CI/CD, test-driven development, and sound architectural principles in all GenAI solutions.

Evaluation Scripts & Load Testing: Develop tests for the random nature of LLM outputs and conduct load testing to ensure system robustness, even when reliant on third-party APIs.

Experience

Individuals from both a data science and data engineering background often excel in this role, given their ability to apply both experimental and engineering mindsets. Ideal candidates:

Have an evaluation mindset and understand the non-deterministic nature of GenAI systems.

Are committed to continuous improvement and quality standards in solutions.

Avoid the “magic box” approach, instead setting clear expectations on performance and accuracy.

Application

To apply, please get in touch with me with your resume @