AI Engineer - Enterprise Applications

About the role

A hands-on AI Engineer is sought to design, develop and deliver enterprise-grade AI applications. The role focuses on application engineering rather than model development, using modern AI technologies to build reliable solutions that meet enterprise requirements for quality, security, performance, scalability and token efficiency. Experience required is 5 to 8 years, full time, working from the office.

Key responsibilities

• Design, develop, test and deploy enterprise-grade AI applications.
• Integrate large language models and AI services with business applications, workflows, APIs, enterprise data sources and systems.
• Build solutions using patterns such as retrieval-augmented generation, semantic search, embeddings, vector retrieval and agentic workflows.
• Develop reusable components, services, prompts, integrations and evaluation workflows.
• Optimise prompts, context, model usage and workflows for token efficiency, latency, response quality and cost.
• Implement security controls, access restrictions, data protection, guardrails and human oversight.
• Set up evaluation and testing for quality, accuracy, relevance, reliability, safety and performance.
• Monitor AI applications in production and troubleshoot quality, latency, integration and resource issues.
• Write maintainable, documented code and collaborate with architects, developers, security and product teams.
• Evaluate emerging AI tools and contribute to code reviews, documentation and engineering standards.

Required profile

• 5 to 8 years of software or application development experience, including production-grade AI applications.
• Experience integrating applications with LLMs, AI platforms, APIs and enterprise data sources.
• Experience building secure, scalable, reliable and high-performing enterprise applications.
• Understanding of AI evaluation, testing, guardrails, observability and production monitoring.
• Experience optimising AI applications for latency, token consumption and cost.
• Knowledge of API development, authentication, authorisation and data security.
• Preferred: agentic AI applications, cloud deployment, containerisation, CI/CD, and responsible AI governance.

Required skills

• Strong programming and software-engineering skills, preferably Python or another backend technology.
• Prompt engineering, context management, RAG, embeddings, semantic search and vector databases.
• API development, authentication and authorisation.