AI Developer

Role: AI Developer

Location: Remote (Aligned with UK time zone)

Experience: 3–5 Years

Role Description

The AI Developer will design, build, and deploy AI-driven solutions that support client products and internal tools. Day-to-day responsibilities include developing and optimizing machine learning models, implementing neural network architectures, and integrating AI components into existing software systems.

The role involves working with natural language processing (NLP), pattern recognition, and data-driven algorithms, as well as collaborating closely with cross-functional teams to translate business requirements into technical solutions. The AI Developer will also maintain and improve model performance, review code for quality and scalability, and contribute to technical documentation and best practices.

Key Responsibilities

AI Development & Solution Delivery

• Design, develop, and deploy AI-powered applications, intelligent agents, and workflow automation solutions for real-world business use cases.
• Build production-ready AI systems using Large Language Models (LLMs), machine learning models, and modern AI frameworks.
• Develop AI agents capable of reasoning, task execution, retrieval, and multi-step workflows.
• Design and implement Natural Language Processing (NLP) solutions including text classification, entity extraction, semantic search, summarization, and conversational AI.
• Build and optimize neural network models for pattern recognition, prediction, and intelligent automation tasks.
• Evaluate AI models for performance, accuracy, scalability, latency, and cost efficiency.

Software Engineering & Integrations

• Develop scalable backend services and APIs to integrate AI capabilities into existing applications and business workflows.
• Build and maintain AI-powered microservices using Python and JavaScript/TypeScript.
• Integrate AI models with third-party platforms, enterprise systems, databases, and cloud services.
• Implement Retrieval-Augmented Generation (RAG) pipelines, vector databases, embeddings, and knowledge retrieval systems where appropriate.
• Ensure production-grade code quality through testing, version control, documentation, and code reviews.

Optimization & Continuous Improvement

• Monitor AI system performance, troubleshoot production issues, and continuously improve model accuracy and reliability.
• Optimize prompts, inference pipelines, and AI workflows to improve response quality and reduce operational costs.
• Maintain technical documentation including architecture diagrams, API documentation, deployment guides, and operational procedures.
• Research emerging AI technologies and recommend new tools, frameworks, and best practices to improve platform capabilities.
• Collaborate with consultants, product teams, and stakeholders to identify new AI opportunities and deliver measurable business value.

Requirements

• Strong software engineering fundamentals including data structures, algorithms, object-oriented programming, and clean coding practices.
• Hands-on experience building AI applications using Python and/or JavaScript/TypeScript.
• Strong understanding of Large Language Models (LLMs) including prompt engineering, context management, tool calling, and AI agent development.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Solid experience in Natural Language Processing (NLP), including text processing, classification, embeddings, semantic search, and conversational AI.
• Experience developing and deploying neural network models for production use cases.
• Strong understanding of REST APIs, JSON, authentication, and backend integrations.
• Experience deploying AI applications on cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Familiarity with containerization technologies such as Docker and modern deployment workflows.
• Experience with Git, CI/CD pipelines, and software development best practices.
• Strong analytical and problem-solving skills with the ability to translate business requirements into scalable AI solutions.
• Ability to work independently while collaborating effectively within a remote engineering team.

Preferred Skills

• Experience building AI agents using OpenAI, Anthropic, LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
• Experience implementing Retrieval-Augmented Generation (RAG) architectures and vector databases such as Pinecone, Weaviate, Chroma, or FAISS.
• Knowledge of model fine-tuning, embeddings, prompt optimization, and AI evaluation techniques.
• Experience integrating AI into enterprise applications using APIs and microservices.
• Familiarity with workflow automation platforms such as n8n, Make, Zapier, or similar tools.
• Experience working with SQL and NoSQL databases.
• Exposure to MLOps practices including model deployment, monitoring, versioning, and lifecycle management.
• Understanding of AI security, responsible AI practices, and data governance.
• Previous experience working in AI consulting, SaaS, or automation-focused environments.

Experience

• 3–5 years of experience in AI development, machine learning engineering, or software engineering with a strong AI focus.
• Proven experience delivering production-ready AI applications and intelligent automation solutions.
• Experience integrating AI models into enterprise software and cloud-based applications.
• Demonstrated experience building scalable AI systems from concept through deployment.
• Portfolio of AI projects, products, or open-source contributions showcasing practical implementation.

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, Artificial Intelligence, or a related field. Equivalent practical experience with a strong portfolio of AI projects will also be considered.

Why Join Us

• Work on cutting-edge AI products and intelligent automation solutions that solve real business problems.
• Build production-ready AI applications using the latest LLMs, machine learning frameworks, and cloud technologies.
• High ownership and end-to-end responsibility across the complete AI development lifecycle.
• Collaborate with experienced engineers, consultants, and business stakeholders in a fast-paced environment.
• Continuous learning opportunities with exposure to emerging AI technologies and modern engineering practices.
• Flexible, remote work environment aligned to UK time zone