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- Tasks: Lead the development of AI solutions using cutting-edge technologies and collaborate with clients.
- Company: Dynamic tech company focused on innovative 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-powered applications.
- Other info: Join a fast-paced environment with excellent career advancement opportunities.
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 hands‑on lead role focused on rapidly prototyping and deploying AI‑powered solutions. Working directly with clients, you will translate their needs into scalable, production‑ready 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 LLM‑powered 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 LLM‑powered applications.
- Proven experience with API‑level 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 third‑party platforms.
- Direct client‑facing 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 production‑grade applications.
- Excellent communication abilities, translating complex technical concepts for diverse audiences.
- Strong analytical and problem‑solving approach, identifying scalable and reusable solutions.
- Leadership qualities, including technical mentorship, team collaboration and line management.
- Ability to align solutions with business goals and industry‑specific constraints.
- Self‑sufficient contributor capable of working independently and seeking support when needed.
Nice to Have
- Deep expertise in some of these areas is preferred over surface‑level 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 Agent‑to‑Agent (A2A).
- LLM evaluation tooling (OpenAI Evals, LangSmith, custom evaluation harnesses).
- Advanced agent patterns: multi‑agent 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 employer: Few&Far Group Ltd
Contact Detail:
Few&Far Group Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field, attend meetups, and join online forums. The more people you know, the better your chances of landing that AI Engineer role.
✨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.
✨Tip Number 3
Prepare for interviews by practising common technical questions related to AI and software engineering. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented AI Engineers like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
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, don’t hold back! Include links or descriptions of your work that demonstrate your ability to build production-ready applications. We love seeing real examples of your skills.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Few&Far Group Ltd
✨Know Your Tech Inside Out
Make sure you’re 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.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled complex challenges in previous roles. Think of examples where you’ve developed scalable AI solutions or improved existing systems. This will demonstrate your analytical abilities and how you align technical solutions with business needs.
✨Communicate Clearly and Confidently
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.
✨Demonstrate Leadership Qualities
Be ready to talk about your experience in mentoring or leading teams. Highlight instances where you’ve collaborated with others or taken initiative in projects. This will show that you can not only contribute technically but also guide and support your team.
