HCLTech

Artificial Intelligence Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Artificial Intelligence Engineer with a contract length of "unknown," offering a pay rate of "unknown." Key skills include expertise in Python, machine learning, deep learning, and experience with cloud platforms like AWS, Azure, or GCP.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
November 18, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Deployment #AI (Artificial Intelligence) #Azure #Python #ML (Machine Learning) #Docker #Cloud #Data Engineering #Microservices #GCP (Google Cloud Platform) #Kubernetes #Databases #AWS (Amazon Web Services) #Scala #Langchain #Automation #Deep Learning
Role description
We are seeking a highly skilled AI Engineer to design, develop, and deploy AI-driven solutions that enhance business processes and customer experiences. The ideal candidate will have strong expertise in machine learning, deep learning, and data engineering, with hands-on experience in building scalable AI models. About the Role • Design, develop, and deploy autonomous AI agents using frameworks like LangChain or LlamaIndex. • Implement agent reasoning, planning, and tool use for executing real-world, multi-step workflows. • Integrate memory systems and RAG (Retrieval-Augmented Generation) using vector databases for context management. • Ensure agent reliability, safety, and governance by establishing robust guardrails and error handling. • Collaborate with product teams to translate complex business needs into agent-based automation solutions. • Monitor, scale, and maintain deployed agents as production microservices on cloud platforms. Required Skills • Expertise in Python and modern software development practices. • Hands-on experience with Large Language Models (LLMs) and advanced prompt engineering. • Familiarity with containerization (Docker/Kubernetes) and CI/CD pipelines. • Knowledge of cloud infrastructure (AWS, Azure, or GCP) for AI service deployment.