AI Platform Engineer

• Leading the design and delivery of AI-enabled enterprise platforms, from early architecture through to production.
• Building and improving applied AI solutions (including LLM-based patterns such as embeddings, retrieval approaches, and model tuning where appropriate).
• Setting engineering standards for MLOps: CI/CD, model deployment, monitoring, evaluation, and operational reliability.
• Architecting secure, cloud-native services (microservices, APIs, messaging/event-driven patterns) that support AI workloads at scale.
• Coaching engineers and collaborating across Engineering, Data Science, and Product to turn complex AI concepts into practical delivery plans.

• Experience building, deploying, and maintaining machine learning and generative AI solutions (e.g., LLMs, embeddings, retrieval patterns, vector search, model fine-tuning).
• Strong MLOps knowledge across continuous integration, deployment, monitoring, and evaluation of AI/ML models.
• Experience with AI infrastructure (orchestration pipelines, GPU compute, model hosting services) and scalable AI data structures (including vector databases/semantic search).
• Deep software engineering capability in .NET Core/C# and modern back-end engineering, with flexibility to work across languages such as Python, Go, or TypeScript.
• Strong understanding of distributed systems, microservices, cloud-native patterns, and modern data stores (SQL and NoSQL).
• Secure coding mindset with awareness of cybersecurity risks, particularly around AI and data privacy.
• Proven technical leadership (principal engineer/tech lead/architect level), with a track record of mentoring and influencing engineering direction.

A leading company is hiring a AI Platform Engineer (MLOps/GenAI). Hybrid position - 6-month rolling contract, paying up to £1100 per day, depending on experience.