AI Engineer at TESTQ Technologies
London, England, United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

05 Oct, 25

Salary

0.0

Posted On

05 Jul, 25

Experience

3 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, Collaborative Environment, Graphql, Machine Learning

Industry

Information Technology/IT

Description

AI Engineer with a strong background in Azure-based AI solutions. Candidate should have hands-on experience working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agent development. Proficiency in Python toolkits is highly preferred. This role offers an opportunity to work on cutting-edge AI projects, leveraging state-of-the-art tools to build intelligent and scalable solutions.

REQUIRED SKILLS & EXPERIENCE:

  • 3+ years of experience in AI/ML engineering.
  • Hands-on expertise with Azure AI services (e.g., Azure OpenAI, Azure Machine Learning, Cognitive Services).
  • Proven experience in working with LLMs, including fine-tuning and prompt engineering.
  • Strong knowledge of RAG techniques and vector search implementation.
  • Experience in designing and deploying AI agents.
  • Proficiency in Python and its AI/ML-related libraries (e.g., TensorFlow, PyTorch, LangChain, Hugging Face, FastAPI).
  • Experience with Vector Databases (e.g., Pinecone, FAISS, Weaviate) and GraphQL (preferred).
  • Familiarity with MLOps practices, CI/CD for AI models, and cloud-based deployment.
  • Strong problem-solving skills and ability to work in a collaborative environment.
Responsibilities
  • Design, develop, and deploy AI solutions leveraging Azure AI services.
  • Implement LLM-powered applications, fine-tuning models for specific use cases.
  • Develop Retrieval-Augmented Generation (RAG) workflows to enhance AI-based search and decision-making.
  • Build and optimize AI agents for automation, recommendation, and conversational AI.
  • Utilize Python toolkits for AI model development, testing, and deployment.
  • Work with cross-functional teams to integrate AI solutions into existing platforms.
  • Ensure scalability, efficiency, and reliability of AI models and pipelines.
  • Stay up to date with advancements in AI, machine learning, and cloud computing.
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