Sr. Associate Director, Software Engineering Specialist

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

Principal Responsibilities:

• Lead the architecture, design and delivery of enterprise-grade AI solutions, ensuring scalability, reliability, security and production readiness.
• Design and develop complex AI agent systems, including agent orchestration, state management, tool integration, fault tolerance and workflow recovery.
• Establish reusable AI engineering capabilities and standards to support adoption across multiple business domains.
• Define AI evaluation and observability frameworks covering task accuracy, execution reliability, safety, latency, cost and operational performance.
• Drive data architecture and governance practices, ensuring data quality, consistency, traceability, security and regulatory compliance.
• Optimise AI application performance through model selection, context management, caching, parallel execution and resource efficiency.
• Design controlled AI execution architectures, balancing autonomous capabilities with deterministic workflows, human oversight and auditability.
• Provide technical leadership through architectural decisions, engineering standards, code reviews and mentoring, working closely with business, architecture and platform teams.

Requirements:

• Bachelor's degree in Computer Science, Engineering or a related field; advanced degree preferred.
• Advanced hands-on Python skills and strong software engineering fundamentals, including distributed systems, asynchronous programming, concurrency and automated testing.
• Proven experience architecting and delivering complex AI applications in production, including LLMs, RAG, tool calling and agent orchestration using frameworks such as LangGraph, LangChain or LlamaIndex.
• Strong expertise in enterprise architecture, distributed systems, API design, event-driven integration and resilient application development.
• Demonstrated experience designing AI evaluation and observability frameworks, including quality assessment, performance monitoring, failure analysis and continuous improvement.
• Strong knowledge of data architecture and governance, including data quality management, metadata, data lineage, access controls and regulatory requirements.
• Experience optimising AI application performance, including model selection, context optimisation, caching, latency reduction and cost efficiency.
• Solid understanding of AI security, responsible AI, deterministic execution, human oversight and auditable decision-making.
• Strong experience with cloud platforms, containerised deployment, CI/CD, production monitoring, troubleshooting and recovery.
• Demonstrated technical leadership in driving architectural decisions, establishing engineering standards, mentoring engineers and delivering complex technical solutions.