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- Tasks: Design and deploy cutting-edge conversational AI products in a dynamic team.
- Company: Join an innovative AI company leading the way in intelligent solutions.
- Benefits: Enjoy a competitive salary and hybrid work options for flexibility.
- Why this job: Be part of a fast-paced environment that values creativity and collaboration.
- Qualifications: Experience with LangGraph, Python, and building chatbots is essential.
- Other info: Initial 6-month contract with potential for extension.
The predicted salary is between 42000 - 63000 £ per year.
NEW CONTRACT AI/ML ENGINEER VACANCY AVAILABLE - HYBRID LONDON
Exciting Opportunity with a Cutting-Edge AI Company
Contract AI Engineer (LLMs / LangGraph / RAG)
6-Month Initial Contract + extension £350-450 Outside IR35 (competitive)
WHO WE ARE
We're working with an innovative organisation at the forefront of AI-powered solutions, focused on building dynamic, intelligent tools for real-time use cases.
THE ROLE
We're seeking AI Engineers to design, build, and deploy conversational AI products using LangGraph, OpenAI functions, and Retrieval-Augmented Generation (RAG) techniques. You'll be part of a hands-on team delivering high-performance AI tools in a fast-paced environment.
WHAT YOU WILL BE DOING
- Building conversational AI flows with LangGraph and OpenAI function-calling
- Integrating live data (e.g., sports data, betting odds) into real-time chat systems
- Developing memory handling, tool usage, and RAG pipelines
- Collaborating on system design, prompt tuning, and architecture decisions
- Optimising AI performance for speed, stability, and user experience
WHAT WE NEED FROM YOU
- Proven experience with LangGraph or LangChain
- Strong Python skills and experience working with LLMs
- Familiarity with RAG pipelines
- Experience building chatbots or agent-based systems
- Knowledge of real-time API integration
- Understanding of prompt engineering, token limits, and system tuning
- Bonus: Experience in sports analytics, fantasy sports, or betting tech
TO BE CONSIDERED…
Please either apply by clicking online or emailing me directly at
KEY SKILLS
- LangGraph
- OpenAI
- Python
- Chatbots
- RAG
- Prompt Engineering
- LLMs
- API Integration
- Sports Data
AI/ML Engineer employer: Searchability
Contact Detail:
Searchability Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer
✨Tip Number 1
Familiarise yourself with LangGraph and OpenAI functions. Dive into their documentation and explore practical examples to understand how they work in real-world applications. This knowledge will help you stand out during discussions.
✨Tip Number 2
Showcase your experience with RAG pipelines by preparing a small project or case study. This could be a chatbot that integrates live data, demonstrating your ability to apply your skills in a practical setting.
✨Tip Number 3
Network with professionals in the AI/ML field, especially those who have experience with conversational AI. Attend meetups or webinars to gain insights and potentially get referrals that can help you land the job.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges in Python, focusing on areas relevant to LLMs and API integration. Being well-prepared will boost your confidence and demonstrate your problem-solving skills.
We think you need these skills to ace AI/ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with LangGraph, Python, and LLMs. Use specific examples of projects where you've built chatbots or worked with RAG pipelines to demonstrate your skills.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for AI and the specific role. Mention how your background aligns with the company's focus on real-time AI solutions and include any relevant experience in sports analytics or betting tech.
Showcase Relevant Projects: If you have any personal or professional projects that involve conversational AI, LangGraph, or API integration, be sure to mention them. Providing links to your GitHub or portfolio can give you an edge.
Proofread Your Application: Before submitting, carefully proofread your application materials. Check for any spelling or grammatical errors, and ensure that all technical terms are used correctly to reflect your expertise.
How to prepare for a job interview at Searchability
✨Showcase Your Technical Skills
Be prepared to discuss your experience with LangGraph, Python, and LLMs in detail. Bring examples of projects you've worked on that demonstrate your ability to build conversational AI products and integrate real-time data.
✨Understand the Role's Requirements
Familiarise yourself with Retrieval-Augmented Generation (RAG) techniques and how they apply to the role. Be ready to explain how you would approach building AI flows and optimising performance for user experience.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving skills. Practice explaining your thought process when tackling challenges related to API integration, memory handling, and prompt engineering.
✨Demonstrate Collaboration Skills
Since the role involves working in a hands-on team, be ready to discuss your experience collaborating on system design and architecture decisions. Highlight any past experiences where teamwork led to successful project outcomes.
