Role Overview
Our client is looking for a highly experienced Principal AI Engineer to lead the engineering and production deployment of advanced AI solutions, including Generative AI applications, LLM-powered systems, AI agents and machine learning platforms.
The role focuses on translating AI research and business requirements into robust, scalable and production-ready applications. The successful candidate will provide hands-on technical leadership, establish AI engineering best practices and work closely with AI architects, product teams, data scientists and software engineers to deliver high-quality AI capabilities.
The ideal candidate will combine deep engineering expertise with practical experience in building, evaluating, deploying and operating AI systems at enterprise scale.
Key Roles & Responsibilities
- Lead the engineering and implementation of enterprise AI and Generative AI applications.
- Develop LLM-powered solutions, RAG pipelines and agent-based workflows.
- Build production-ready AI services using scalable software engineering principles.
- Design model evaluation frameworks to measure accuracy, reliability and business effectiveness.
- Develop data processing, embedding generation and retrieval pipelines.
- Implement prompt engineering, context management and AI orchestration strategies.
- Integrate AI models with enterprise APIs, databases and business applications.
- Optimise inference performance, latency, scalability and operational costs.
- Establish automated testing, CI/CD and deployment practices for AI applications.
- Implement observability, monitoring, guardrails and failure-handling mechanisms.
- Collaborate with architecture, product, data and security teams.
- Mentor senior engineers and establish reusable AI engineering standards.
- Evaluate emerging AI models, frameworks and technologies for enterprise adoption.
Preferred Qualifications
- Bachelor's or master's degree in Computer Science, AI, Machine Learning or a related field.
- 10–15+ years of software engineering or AI-related experience.
- Strong hands-on experience building and deploying AI or machine learning applications.
- Demonstrated expertise in Generative AI and production LLM systems.
- Experience leading complex technical initiatives and mentoring engineering teams.
Key Skills & Attributes
- Advanced software engineering and system design.
- Generative AI and LLM application development.
- RAG architecture and retrieval optimisation.
- Model evaluation and performance tuning.
- Production deployment and AI observability.
- Technical problem-solving and engineering leadership.
- Ability to balance innovation with reliability and maintainability.
Technical Skills
- Python and modern software engineering practices.
- PyTorch, TensorFlow or equivalent machine learning frameworks.
- LLM APIs and open-source language models.
- LangChain, LlamaIndex or equivalent orchestration frameworks.
- Vector databases and semantic search.
- REST APIs, microservices and distributed systems.
- Docker, Kubernetes and cloud-native deployment.
- CI/CD, automated testing and MLOps/LLMOps.
- Model monitoring, evaluation and AI safety guardrails.
- AWS, Azure or Google Cloud AI services.
Reporting / Team Relationships
Works closely with:
- CTO / VP of Engineering
- AI Architect and Enterprise Architects
- AI and Machine Learning Teams
- Data Engineering Teams
- Product Management Team
- Cloud, DevOps and Security Teams
What the Role Offers
This is a senior technical leadership opportunity for an AI engineering professional who wants to shape the future of Generative AI, intelligent applications and advanced AI solutions.
The successful candidate will play an important role in transforming AI concepts into scalable, production-ready applications, developing advanced AI capabilities and establishing engineering practices that improve performance, reliability and business value.
The role offers an opportunity to influence technical direction, mentor engineering teams and contribute to the development of innovative AI-driven products.
