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structures, API contracts, and code quality across Java, Python & OCI technology stacks.\nLead architecture review boards, design critiques, and technical risk assessments for major initiatives.\nDrive the adoption of AI/ML capabilities - including LLMs, predictive analytics, and intelligent automation - into core business workflows.\nEnsure solutions meet non-functional requirements: high availability, performance, observability, and security compliance.\nAI & Data Engineering\nDefine the strategic vision and execution roadmap for AI-based application development across core Business System use cases.\nChampion responsible AI practices, including model governance, explainability, bias mitigation, and auditability in regulated financial environments.\nStay ahead of the curve on emerging AI frameworks, foundation models, and agentic system design patterns.\nEngineering Delivery & Programme Management\nOwn end-to-end delivery accountability for multiple concurrent technology programmes, ensuring on-time, on-budget, and high-quality outcomes.\nApply best practices in Agile/SAFe delivery, managing backlogs, sprint cadences, release planning, and stakeholder reporting.\nIdentify, track, and mitigate project risks, dependencies, and delivery bottlenecks proactively.\nManage vendor and partner relationships, including contract oversight and SLA governance.\nTeam Leadership & People Development\nBuild, manage, and inspire a multi-disciplinary engineering team across software engineers, architects, data engineers, and QA professionals.\nDefine career growth frameworks, conduct performance reviews, and create individual development plans aligned to team and organisational goals.\nFoster a culture of psychological safety, continuous learning, and engineering excellence.\nDrive talent acquisition and succession planning in partnership with HR and Talent Acquisition.\nStakeholder & Executive Engagement\nServe as the primary technology partner to C-suite and senior business stakeholders (CFO, CPO, COO offices), translating complex technical concepts into business value narratives.\nPrepare and present technology roadmaps, investment cases, programme status updates, and risk registers at Board and Executive Committee level.\nInfluence strategic technology decisions and enterprise architecture direction through credible, data-driven recommendations.\nBuild strong cross-functional partnerships with Product, Finance, Operations, Risk, and Compliance teams.\nRequired Qualifications & Experience\nExperience\n15-17 years of progressive experience in software engineering and technology leadership roles within enterprise environments.\nMinimum 5 years in a senior leadership role managing multi-functional engineering teams of 15 or more.\nDomain Knowledge\nDeep functional understanding of major Finance & Revenue, Project & Delivery management, ITSM & IT operations, HR & workforce and Customer experience processes\nFamiliarity with regulatory and compliance frameworks relevant to Finance technology (e.g., SOX, IFRS, GAAP).\nTechnical Expertise\nExpert-level proficiency in Java (Spring Boot, microservices, JVM performance tuning) and Python (FastAPI, Django, data engineering libraries such as Pandas, PySpark).\nHands-on experience designing and building AI-based applications, including LLM integration, RAG architectures, ML pipelines, and intelligent automation workflows.\nStrong command of data structures, algorithms, distributed systems, and system design principles including CQRS, Event Sourcing, and Domain-Driven Design.\nExtensive experience with cloud-native architectures on OCI & AWS; containerisation (Docker, Kubernetes), CI/CD pipelines, and DevSecOps practices.\nProficiency in relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, Cassandra) and data warehouse/lakehouse technologies (Snowflake, Databricks, BigQuery).\nFamiliarity with enterprise integration patterns, API management platforms, and event streaming (Kafka, 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