Ai Developer

Description:

A forward-thinking and fully remote technology company is seeking a Python/AI Developer to lead and deliver high-impact technical work across diverse projects involving large language models (LLMs), vector search, and modern AI tooling. This is a hands-on, full-time remote position open to candidates based in the UK or EU, offering an exciting opportunity to work at the cutting edge of artificial intelligence.

As a Python/AI Developer, you will contribute to both client-facing projects and internal product development, taking ownership of AI-driven systems and pipelines. You will be responsible for designing, building, and evaluating real-world AI solutions using the latest models, frameworks, and tooling. The role also involves cross-functional collaboration with developers, strategists, and designers to ensure robust and scalable delivery.

Key Responsibilities:

• Design, develop, and maintain Python-based microservices and AI systems

• Integrate LLMs through APIs and open-source frameworks

• Implement and evaluate prompt engineering and LLM response pipelines

• Prepare and manage large-scale text datasets for training and inference

• Deploy and manage vector databases for semantic search (e.g., Pinecone, Chroma)

• Architect and deploy AI pipelines and services for production use

• Collaborate with cross-functional teams for seamless technical delivery

• Write technical documentation and uphold high development standards

Required Skills and Experience:

• Strong proficiency in Python and relevant ML/AI libraries

• Experience working with LLM APIs (e.g., OpenAI, Cohere) and open-source models

• Knowledge of prompt engineering and model evaluation techniques

• Familiarity with vector databases such as Pinecone or Chroma

• Experience with cloud-based AI platforms, especially AWS Bedrock

• Comfortable deploying production services with REST APIs

• Ability to independently design and execute complex technical solutions

• Excellent communication and documentation capabilities

Nice to Have:

• Experience with Retrieval-Augmented Generation (RAG) pipelines

• Exposure to model training, fine-tuning, or hosted open-weight models

• Familiarity with containerization (Docker), serverless deployment, or cloud infrastructure

• Previous hands-on experience delivering production-level AI systems