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For Companies At a Glance
- Tasks: Lead the development of AI solutions using cutting-edge technologies and collaborate with clients.
- Company: Innovative tech firm focused on AI applications across various industries.
- Benefits: Remote work, competitive pay, and opportunities for professional growth.
- Why this job: Make a real impact by solving industry challenges with AI technology.
- Qualifications: 5+ years in software engineering with experience in LLM applications and client interaction.
- Other info: Join a dynamic team with a focus on innovation and career advancement.
The predicted salary is between 36000 - 60000 ÂŁ per year.
The successful AI Solutions Engineer will extend and enhance our AI Operating System, which leverages LLMs to solve industry-specific challenges across defence, legal, health, infrastructure and management consulting sectors. This is a handsâon lead role focused on rapidly prototyping and deploying AIâpowered solutions. Working directly with clients, you will translate their needs into scalable, productionâready AI applications using modern frameworks and techniques.
Duties & Responsibilities
- Develop platform functionality using Python, building APIs and integrations to extend capabilities for diverse client needs.
- Design and implement LLMâpowered applications and workflows using open source models such as Llama, Qwen and Gemma, as well as online models from OpenAI, Gemini, etc.
- Build AI agents with tool/function calling, prompt engineering and appropriate guardrails using frameworks such as OpenAI AgentSDK, LangGraph or LlamaIndex.
- Implement testing and evaluation frameworks for LLM applications, covering prompt testing, output quality metrics and agent behaviour validation.
- Apply relevant AI technologies as needed, including retrieval systems (RAG, GraphRAG), knowledge graphs, vector databases or data pipelines.
Role Requirements
- At least five years as a software engineer on commercial platforms, with demonstrable experience building production LLMâpowered applications.
- Proven experience with APIâlevel LLM usage, including tool/function calling, prompt engineering and evaluation.
- Experience with agent frameworks (OpenAI AgentSDK, LangGraph, LlamaIndex Agents or similar).
- Experience developing APIs using FastAPI or similar frameworks and integrating with thirdâparty platforms.
- Direct clientâfacing experience gathering requirements and delivering technical implementations.
- Experience within agile development workflows and engineering teams.
Skills & Abilities
- Strong Python (or similar) programming skills with a focus on productionâgrade applications.
- Excellent communication abilities, translating complex technical concepts for diverse audiences.
- Strong analytical and problemâsolving approach, identifying scalable and reusable solutions.
- Leadership qualities, including technical mentorship, team collaboration and line management.
- Ability to align solutions with business goals and industryâspecific constraints.
- Selfâsufficient contributor capable of working independently and seeking support when needed.
Nice to Have
- Deep expertise in some of these areas is preferred over surfaceâlevel knowledge across all domains.
- Open source LLMs (Llama, Qwen, Gemma, GPT OSS) and local deployment strategies.
- Frameworks and protocols such as Model Context Protocol (MCP) or AgentâtoâAgent (A2A).
- LLM evaluation tooling (OpenAI Evals, LangSmith, custom evaluation harnesses).
- Advanced agent patterns: multiâagent systems, supervision, delegation strategies.
- RAG, GraphRAG and knowledge graph design and implementation.
- Vector databases and similarity search systems.
- Graph databases (ArangoDB, Neo4j, Neptune) and property graph modelling.
- Data engineering: ETL pipelines, document processing, schema design for AI applications.
- Cloud platforms (GCP preferred, AWS/Azure also relevant) and containerisation (Docker).
- Observability and monitoring for LLM applications (tracing, metrics, cost tracking).
- Secure coding practices for regulated industries and sensitive data handling.
AI Engineer in London employer: Few&Far Group Ltd
Contact Detail:
Few&Far Group Ltd Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land AI Engineer in London
â¨Tip Number 1
Network like a pro! Reach out to your connections in the AI field and let them know you're on the hunt for an AI Engineer role. You never know who might have the inside scoop on a job opening or can refer you directly.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs and Python. This will give potential employers a taste of what you can do and set you apart from the crowd.
â¨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with APIs, prompt engineering, and client interactions. Practice makes perfect!
â¨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find the right opportunities and connect with us directly. Plus, it shows you're serious about joining our team!
We think you need these skills to ace AI Engineer in London
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV is tailored to the AI Engineer role. Highlight your experience with LLMs, Python, and any relevant frameworks. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your past experiences make you a great fit for our team. Keep it engaging and personal.
Showcase Your Projects: If you've worked on any cool AI projects, donât forget to mention them! Whether it's building APIs or developing LLM applications, we love seeing real examples of your work.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you get all the updates directly from us!
How to prepare for a job interview at Few&Far Group Ltd
â¨Know Your Tech Inside Out
Make sure youâre well-versed in the technologies mentioned in the job description, especially Python and LLM frameworks. Brush up on your experience with API development and integration, as you'll likely be asked to discuss specific projects where you've applied these skills.
â¨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled complex challenges in previous roles. Think of examples where youâve designed scalable AI solutions or improved existing systems. This will demonstrate your analytical abilities and how you can contribute to their projects.
â¨Communicate Clearly
Since this role involves client interaction, practice explaining technical concepts in simple terms. You might be asked to translate complex ideas for non-technical stakeholders, so being able to communicate effectively is key.
â¨Demonstrate Leadership Qualities
Be ready to talk about your experience in mentoring or leading teams. Highlight instances where youâve collaborated with others or taken charge of a project. This will show that you can not only work independently but also guide others in a team setting.
