Own the full lifecycle of AI projects-from ideation and data collection to production deployment and post-launch evaluation.
Write well-designed, efficient, and testable code that integrates directly into product codebases
Implement Model Context Protocol (MCP) to connect LLMs with proprietary data sources and internal tools securely
Scope and build Generative AI solutions using a mixture of SaaS (OpenAI, AWS Bedrock) and Open Source solutions.
Work with development, QA, and infrastructure teams to scale and monitor AI solutions in production

3+ years of experience in a production ML/AI engineering role.
Proven experience writing production-grade Python code and deploying ML models at scale.
Ability to work cross-functionally and a track record of continuous learning in the rapidly evolving AI space
Hands-on experience building and deploying applications with multiple LLM providers (OpenAI, Anthropic, Google, AWS Bedrock)
Experience with open-source LLMs (e.g., Llama, Mistral) including deployment and/or fine-tuning
Demonstrated ability to take AI features from prototype through to production
Solid software engineering fundamentals
CI/CD, testing, containerisation, cloud deployment
Full lifecycle ML experience: data, training/prompting, evaluation, deployment, monitoring

Senior AI/ML Developer

Key skills