At a Glance
- Tasks: Lead the development of AI solutions using cutting-edge technologies to solve real-world challenges.
- Company: Join a forward-thinking tech company focused on AI innovation.
- Benefits: Enjoy remote work, competitive pay, and opportunities for professional growth.
- Other info: Dynamic, agile environment with strong potential for career advancement.
- Why this job: Make a tangible impact in diverse sectors while working with advanced AI technologies.
- Qualifications: 5+ years in software engineering with experience in LLM applications and client-facing roles.
The predicted salary is between 36000 - 60000 £ 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
- Technical Development
- 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 those 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
- Work Experience
- 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 in Southampton employer: Few&Far
Join a forward-thinking company that values innovation and collaboration, offering AI Engineers the opportunity to work remotely across the UK. With a strong focus on employee growth, we provide access to cutting-edge technologies and encourage continuous learning in a supportive environment. Our culture promotes teamwork and creativity, ensuring that your contributions directly impact diverse sectors such as defence and healthcare.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer in Southampton
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI field, attend meetups, and join online forums. You never know who might have the inside scoop on job openings or can refer you directly.
✨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 brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with clients and team members.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace AI Engineer in Southampton
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 background makes you a perfect fit for our team. Keep it engaging and personal.
Showcase Your Projects:If you've worked on any cool AI projects, make sure 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 directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Don’t miss out!
How to prepare for a job interview at Few&Far
✨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 APIs and any specific tools like OpenAI AgentSDK or LangGraph. Being able to discuss your past projects in detail will show that you’re not just familiar with the tech, but you’ve actually used it effectively.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Use examples that highlight your analytical skills and ability to create scalable solutions. This is particularly important for an AI Engineer role where innovative problem-solving is key.
✨Communicate Clearly and Confidently
Since this role involves direct client interaction, practice explaining complex technical concepts in simple terms. You want to demonstrate that you can bridge the gap between technical jargon and client understanding. Role-play with a friend or colleague to refine your communication style.
✨Be Ready for Hands-On Challenges
Expect practical assessments or coding challenges during the interview. Brush up on your coding skills and be prepared to solve problems on the spot. Familiarise yourself with common algorithms and data structures, as well as the specific frameworks mentioned in the job description.
