Description
We are seeking an experienced AI Platform Engineer to lead and manage engineering teams, providing technical guidance, mentorship, and support to ensure the delivery of high-quality software solutions. You will drive technical excellence, foster a culture of innovation, and collaborate with cross-functional teams to align technical decisions with business objectives.
Responsibilities
- Lead engineering teams effectively, fostering a collaborative and high-performance culture to achieve project goals and meet organisational objectives.
- Oversee timelines, team allocation, risk management, and task prioritisation to ensure successful delivery of solutions within scope, time, and budget.
- Mentor and support team members' professional growth, conduct performance reviews, provide actionable feedback, and identify opportunities for improvement.
- Evaluate and enhance engineering processes, tools, and methodologies to increase efficiency, streamline workflows, and optimise team productivity.
- Collaborate with business partners, product managers, designers, and other stakeholders to translate business requirements into technical solutions and ensure a cohesive approach to product development.
- Enforce technology standards, facilitate peer reviews, and implement robust testing practices to ensure high-quality solutions.
Vice President Expectations
- Contribute to or set strategy, drive requirements, and make recommendations for change.
- Plan resources, budgets, and policies; manage and maintain policies/processes; deliver continuous improvements and escalate breaches of policies/procedures.
- Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work of your team.
- Demonstrate comprehensive understanding of the organisation's functions to contribute to achieving business goals.
Requirements
- Experience with Cloud Platform Engineering (Azure preferred), including Kubernetes, containerisation, Infrastructure as Code (Terraform/Bicep), and platform operations.
- Experience with Software Engineering & API Development using Python and/or Java, with experience building scalable services, APIs, and integration frameworks.
- Experience with AI Platform & MLOps Engineering, including deployment and operationalisation of LLMs, model lifecycle management, prompt orchestration, vector databases, and AI observability.
- Experience with DevSecOps & Enterprise Security, including CI/CD pipelines, automated testing, secrets management, vulnerability remediation, and secure-by-design engineering practices.
Nice to Have
- Financial Services Domain Knowledge, particularly Payments, Cash Management, Liquidity, Treasury, or Transaction Banking platforms.
- Data Engineering & Analytics, including data pipelines, data quality controls, metadata management, and retrieval-augmented generation (RAG) architectures.
- AI Governance & Risk Management, including model risk controls, AI guardrails, responsible AI practices, and regulatory compliance requirements.
- Site Reliability Engineering (SRE) & Platform Operations, including monitoring, resiliency engineering, incident management, capacity planning, and operational excellence.