Principal AI Engineer

About This Opportunity

Our talent team is representing a confidential enterprise SaaS organization seeking a Principal AI Engineer for their London office. This role sits at the intersection of machine learning and software engineering, building production-ready generative AI features that empower business users. You'll work across the full stack—from model integration and prompt engineering to API development and deployment—creating AI capabilities that integrate seamlessly into enterprise planning workflows.

Responsibilities

• Lead the architecture, design, and deployment of scalable Generative AI and Machine Learning systems into production environments
• Develop end-to-end GenAI features including backend API services, model integration, monitoring, evaluations, and deployments
• Integrate and optimize LLMs for specific business use cases, including prompt engineering and RAG implementation
• Build conversational interfaces and agentic workflows that make complex tasks accessible through natural language
• Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics
• Design and develop APIs that expose AI capabilities to platform integrations and third-party systems
• Optimize model inference pipelines for performance, cost, and scalability in production environments
• Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behavior
• Collaborate with data scientists to productionize ML models and forecasting algorithms

What We're Looking For

Required Skills:

• Extensive hands-on professional experience in Artificial Intelligence, Machine Learning, or related engineering domains
• End-to-end exposure in model lifecycle development, with extensive experience training and deploying ML models in production environments
• Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns
• Experience fine-tuning LLMs for domain-specific enterprise applications
• Strong expertise in MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments
• Experience with agentic frameworks and autonomous agent architectures
• Proficiency in Python and modern software development practices (testing, code review, CI/CD)
• Proven track record of delivering complex technical projects on time with high quality

Desirable Qualifications:

• Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a strongly related quantitative field
• Hands-on experience with cloud-native ML infrastructure platforms
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models
• Experience with model serving frameworks (vLLM, TensorRT, Ray)
• Experience with A/B testing and experimentation frameworks for AI features
• Contributions to open-source ML projects or research publications
• Experience with model observability tools (LangSmith, W&B, MLflow)

How We Work With You

Candidates apply directly through Get A Job.ai. Our recruiting team conducts an initial screening to understand your background and ensure alignment with the role requirements. Once we confirm you're a strong match, we submit your profile to our client for consideration and coordinate all subsequent interview stages. Please do not contact the client directly—all communication regarding this opportunity should flow through Get A Job.ai to ensure a smooth process for everyone involved.

Pay

Compensation details will be discussed during the screening process based on your experience and qualifications.

Equal Employment Opportunity

Get A Job.ai is committed to fair and equitable recruiting practices. We welcome candidates of all backgrounds and provide reasonable accommodations throughout our hiring process.