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EscalentPosted 2 months ago

AI Transformation Developer

On-siteLondon, England, United Kingdom

Full Time

Job Summary

AI Transformation Developer responsible for designing, developing, and deploying AI-powered applications and intelligent workflows using Python in a cloud-native environment. Responsibilities include building RESTful APIs and microservices to integrate AI models and external tools, constructing data pipelines for structured and unstructured data, enabling retrieval-based and prompt-driven AI experiences (semantic search and contextual responses), optimizing performance for scalability and reliability, collaborating with cross-functional teams, applying security/testing/CI/CD best practices, debugging across application logic and model integrations, writing clean, well-documented code, and staying current with emerging AI technologies and Python frameworks.

Required Qualifications

  • 5-8 years of Python development experience, with 2+ years of AI/ML development
  • Strong proficiency in Python and experience with frameworks such as Django, Flask, or FastAPI
  • Experience with API development, integration, and web services in production environments
  • Hands-on experience integrating AI or ML models, LLM APIs, or automation frameworks into applications
  • Strong knowledge of database systems including SQL, NoSQL, and data storage patterns for AI applications
  • Familiarity with cloud platforms such as AWS and Azure, and containerization technologies including Docker and Kubernetes
  • Understanding of asynchronous programming, performance optimization, and scalable backend architectures
  • Experience with unit testing, debugging, version control, and software engineering best practices
  • Familiarity with data processing, prompt-driven workflows, semantic search, or retrieval-based AI patterns is a strong plus
  • Ability to work effectively in a collaborative team environment with strong problem-solving and execution skills
  • Desirable Skills
  • Experience working with Agile development methodologies
  • Familiarity with DevOps and MLOps practices, including CI/CD pipelines, infrastructure automation, and deployment workflows
  • Exposure to vector databases, embeddings, or orchestration frameworks used in modern AI applications
  • Strong written and verbal communication skills with the ability to document technical solutions clearly

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