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⚡ Source: ReedRef: 56729579

Software Engineer (GenAI)

AJ Bell·Salford·Posted 1 months ago
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Job description

Original text imported from Reed

Job Description

This is an fantastic opportunity for a Software Developer (GenAI) to join at an exciting time for AJ Bell as we expand the usage of AI within the business. Our GenAI development team are at the heart of this growth and ee have a strong team working environment, training and excellent career progression for the right person.

Our strategy is to have a cross-functional development team, with team members working on all areas of our technology stack and propositions.

What we're looking for:

We’re seeking an energetic and driven software developer with strong skills and/or interest in Generative AI and large language models to help us deliver cutting-edge GenAI solutions across our business. This is a unique opportunity to not only work with advanced AI technologies but also build and deliver innovative solutions for our business and stakeholders. People who are excited by GenAI technology, love pushing the boundaries of what's possible while at the same time keeping an eye on the bigger picture and ensuring the best outcomes for our stakeholders by providing straightforward but robust solutions.

Key technical skills:

  • Strong knowledge and deep experience of Python programming, libraries and toolchains
  • Familiarity with large language models (LLMs) like GPT, Gemini, and open-source models such as Lama and MRR
  • Solid understanding of RESTful API design and implementation
  • Git based source control and JIRA

Bonus points for:

  • Knowledge/experience working with Cloud, preferably AWS
  • Knowledge of AI/ML and latest AI trends & technologies
  • Familiarity in LLM frameworks and libraries such as LangChain, Langfuse, LiteLLM
  • CI / CD / Docker / Kubernetes

Soft skills:

  • Agile / SCRUM
  • Strong technical, problem solving and communication skills
  • Keen to learn and develop new technical& non-technical skills
  • Passionate, self-starting, flexible and enjoy working in fast-paced environments

About AJ Bell

AJ Bell is one of the UK’s fastest-growing investment platform businesses, providing award-winning solutions for everyone, from professional financial advisers to first-time investors.

Today, over 644,000 customers trust us to manage more than £103.3 billion of assets. By continually striving to make investing simpler and more accessible, we’re helping more people take control of their financial futures.

We’re proud to be recognised as one of the UK’s Best 100 Companies to Work For for six consecutive years, and a Great Place to Work in 2025 and 2026 a reflection of our supportive and collaborative culture.

What we offer

  • Starting salary of ....
  • 25 days holiday, increasing with service + buy/sell scheme + bank holidays
  • 6% Pension with matched contributions
  • Discretionary bonus scheme
  • Share schemes (including free shares and BAYE)
  • Health Cash Plan and discounted private healthcare
  • Free onsite gym
  • Enhanced family leave (subject to qualifying criteria)
  • Travel and bike loan schemes
  • Employee Assistance Programme

Life at AJ Bell

  • Regular social events including summer and Christmas parties
  • Learning and development opportunities tailored to you
  • Casual dress code
  • Friendly, supportive team environment

Our ways of working

We offer hybrid working, with a minimum of 50% of your working time per month spent in the office.

For new starters, there’s an initial period of full-time office working to help you settle in and build relationships.

Inclusion & diversity

We’re committed to creating an inclusive environment where everyone feels respected and able to be themselves at work.

We welcome applications from all backgrounds and make hiring decisions based on skills, experience and potential.

SpeedCV AI

Key skills

AI-extracted from the job advert

Must-have skills
Python programmingLarge Language ModelsRESTful API designGit version controlJIRA
Nice-to-have
AWSLangChainLangfuseLiteLLMDockerKubernetesCI/CD
Soft skills
Problem solvingCommunicationSelf-motivationFlexibilityAdaptabilityCollaborationLearning agility
SpeedCV AI

Application advice

5 AI-generated recommendations to maximise your chances.

1

⭐ Highlight your Python programming experience prominently as this is the core technical requirement mentioned multiple times

2

🤖 Showcase specific LLM projects or experience with GPT, Gemini, or open-source models like Lama to demonstrate GenAI expertise

3

☁️ Emphasise any AWS cloud experience as bonus points, particularly if you've deployed AI/ML models in cloud environments

4

🔧 Detail your experience with LLM frameworks like LangChain or Langfuse to stand out from other candidates

5

📊 Quantify your API development work: "Built 15 RESTful endpoints serving 10k+ daily requests"

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Suggested CV bullets

3 bullets our AI drafted for this specific advert, mirroring its ATS keywords.

How to tailor your CV

Add these 3 bullets under your most recent experience:

  • Developed 12 Python-based GenAI applications using LangChain framework, reducing processing time by 45% for 8,000+ daily user queries
  • Built RESTful APIs serving GPT-4 and Gemini models with 99.7% uptime, handling 25,000+ requests per day across 6 business units
  • Implemented CI/CD pipelines for LLM deployments on AWS, cutting release cycles from 3 weeks to 2 days while maintaining zero-downtime deployments

Free to copy — tailoring requires a 30-sec CV upload.

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Letter preview — tailored to AJ Bell

Dear Hiring Manager,

AJ Bell's expansion into GenAI technology represents exactly the career direction I want to pursue, particularly your focus on delivering cutting-edge solutions with Python and large language models across your £103.3 billion investment platform.

My background in Python development and experience with LLM frameworks like LangChain positions me well to contribute to your cross-functional GenAI team. I'm particularly drawn to the opportunity to work with both proprietary models like GPT and open-source alternatives while building robust RESTful APIs.

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SpeedCV AI

Interview questions

10 questions generated from this advert.

Technical

  • How would you approach fine-tuning a large language model for financial services use cases?
  • Explain the differences between GPT, Gemini, and open-source models like Lama in terms of implementation
  • How would you design a RESTful API to serve LLM responses with proper error handling?
  • What considerations would you make when deploying GenAI models on AWS infrastructure?
  • How would you implement monitoring and observability for LLM applications using tools like Langfuse?

Behavioural

  • Tell me about a time you had to learn a new technology quickly to deliver a project
  • Describe a situation where you had to solve a complex technical problem with limited resources
  • How do you stay current with rapidly evolving AI technologies and trends?
  • Give an example of when you had to communicate complex technical concepts to non-technical stakeholders
  • Tell me about a time you worked in a cross-functional team to deliver a solution
SpeedCV AINEW

STAR answer examples

Model answers using the Situation-Task-Action-Result framework. Adapt to your own experience.

1Question

Tell me about a time you had to learn a new technology quickly to deliver a project

When our team needed to integrate GPT-4 API into our customer service platform within 6 weeks, I had no prior LLM experience. I dedicated 2 hours daily to studying OpenAI documentation and LangChain tutorials, built 3 prototype applications over 2 weeks, and collaborated with our data team to create training datasets. I successfully delivered the integration 3 days ahead of schedule, resulting in 40% faster response times and 92% customer satisfaction scores. This experience taught me the importance of structured learning and hands-on experimentation when adopting new technologies.
2Question

How do you stay current with rapidly evolving AI technologies and trends?

I maintain a structured approach to staying current with AI developments through multiple channels. I subscribe to 4 key AI research publications, attend monthly London AI meetups, and dedicate Friday afternoons to experimenting with new frameworks like Langfuse and LiteLLM. Recently, I built a personal project comparing 3 open-source models against GPT-4 for text summarisation, which helped me understand their practical differences. I also participate in our team's weekly tech talks where we share findings from conferences and research papers, ensuring our entire 8-person team stays aligned on emerging trends.

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