AI Engineering Platform Lead

Responsibilities

• Define and execute the corporate AI strategy and roadmap, aligning with business objectives and digital initiatives. Champion the establishment of AI software engineering standards and adoption of AI-assisted coding frameworks to enhance software development agility. Evaluate emerging technologies, platforms and solutions for competitive advantage.
• Design, develop, and oversee the implementation of scalable, secure, and reliable AI platforms for efficient agent integration. Lead deployment of advanced AI components, including Large Language Models (LLMs), RAG, and agentic workflows.
• Develop and deploy AI-assisted tools (like MCP platforms) into existing development processes. Establish best practices to facilitate frictionless developer workflows, enhancing productivity through AI-powered testing, deployment, and coding tools.
• Establish and maintain LLMOps and AgentOps standards for model lifecycle management. Implement robust monitoring, observability, and quality assurance to ensure reliability and performance.
• Define enterprise architecture standards and design patterns for responsible AI. Lead governance forums to ensure AI solutions comply with cybersecurity, regulatory, and ethical standards, maintaining strong controls for data protection and explainability.
• Evaluate and recommend AI platforms and third-party solutions. Support vendor due diligence and collaborate with leadership and business units to prioritize initiatives and drive AI literacy across the enterprise.

Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related discipline. Master's degree in AI, Machine Learning, Data Science, or a related field is preferable.
• Around 10+ years of experience in software engineering and solution architecture, with at least 3+ years of hands-on experience in AI, Machine Learning, or Generative AI.
• Proven track record of delivering enterprise-grade AI solutions in regulated environments such as banking, financial services, fintech, or large corporate settings.
• Deep hands-on experience with Generative AI (LLMs, RAG, agentic workflows, prompt engineering) and strong software engineering skills (Python, Java, RESTful APIs, microservices).
• Solid experience designing scalable, secure, and reliable enterprise architecture. Familiarity with cloud platforms, LLMOps, and the ability to build robust backend systems and application platforms is essential.
• Demonstrated experience establishing AI governance, production monitoring, and secure AI deployment standards, with a strong understanding of model governance, data security, and compliance.
• A self-motivated problem-solver who thrives under pressure and is passionate about building reliable and scalable systems.
• Excellent communication skills (both verbal and written) to influence senior stakeholders.

We offer successful candidate an attractive remuneration package and excellent career prospects. Interested parties please send your resume, present and expected salary, contact details and quoting the reference number by clicking "

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Octopus is an equal opportunity employer and all employment decisions and Human Resources policies are administered; especially those relating to recruitment & selection, compensation & benefits, promotion & transfer, training & development and termination & redundancy; without discrimination on the basis of age, race, colour, religion, sex,national origin, marital status, pregnancy, physical and mental disability and family status but on genuine occupational qualification, job performance, employees' ability and internal/ external relativities.