Associate Director, Software Engineering

We are currently seeking an experienced professional to join our team in the role of Associate Director, Software Engineering.

Principal responsibilities:

• Lead the evaluation and adoption of AI and ML technologies for CEAIA, with a focus on LLM, agentic AI, RAG, knowledge management, and emerging engineering patterns.
• Drive technical research, proof-of-concept development, and prototype delivery to validate new ideas and accelerate platform evolution.
• Define solution approaches and engineering patterns for AI use cases, ensuring they are scalable, maintainable, and aligned with enterprise standards.
• Partner with development teams to refine solution details, unblock technical issues, and support high-quality implementation across the delivery lifecycle.
• Contribute to the design and improvement of knowledge base, retrieval, memory, orchestration, and search capabilities that enhance CEAIA platform effectiveness.
• Work hands-on with technologies such as Python, PostgreSQL, APIs, vector databases, and cloud services to support solution design and delivery.
• Establish strong engineering practices across evaluation, testing, CI/CD, observability, and operational readiness for AI-enabled solutions.
• Work with stakeholders across business, product, architecture, and technology teams to identify opportunities, assess feasibility, and prioritise high-value innovation areas.
• Collaborate across multiple sites and different departments to drive alignment, delivery progress, and technical consistency.
• Provide technical leadership and practical guidance to engineers, helping raise the standard of AI engineering across the team.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related discipline.
• 10+ years of experience in relevant technologies, with strong hands-on delivery experience across AI, ML, data, and enterprise technology solutions.
• Strong hands-on experience in AI and ML engineering, with a track record of delivering innovative solutions from concept through implementation.
• Deep knowledge of LLM and agent-based solution design, including prompt engineering, Agentic RAG, knowledge retrieval, memory design, and orchestration patterns.
• Experience building or improving knowledge management and knowledge base solutions for structured and unstructured content, including document parsing, indexing, retrieval, and search optimisation.
• Good understanding of machine learning and deep learning techniques, such as model training, fine-tuning, multimodal AI, computer vision, NLP, or speech-related applications.
• Strong hands-on experience with Python and solid working knowledge of PostgreSQL and related data technologies.
• Experience working with modern AI and engineering ecosystems, such as open-source AI frameworks, vector databases, APIs, and cloud platforms including AWS, Azure, or GCP.
• Strong prototyping and research capability, with the ability to assess emerging technologies and translate them into practical engineering solutions.
• Solid software engineering discipline, including testing, CI/CD, performance optimisation, observability, and production support considerations.
• Strong verbal and written English communication skills, with the ability to work effectively across multiple sites, cross-functional teams, and different business and technology departments.
• Proven ability to collaborate with stakeholders across regions and functions, align diverse requirements, and drive delivery in a complex enterprise environment.