Senior Genai Engineer Global Link ,vice President

Job Title

The ideal candidate will be responsible for:

• Implementation and delivery of new server-side components, microservices, Web APIs, and enhancements to the BestX product.
• Exhibiting superior skills across modern Agile engineering, cloud-native architectures, server-side development, and database design.
• Developing a strong understanding of Transaction Cost Analysis (TCA) and the key benchmarks required for MiFID II / MiFIR.
• Maintaining and enhancing core applications while influencing and shaping technology and architectural decisions.
• Taking full ownership of tasks and seeing them through to completion with a strong sense of accountability and quality.
• Establishing and enforcing best practices, including clean code, robust design patterns, and maintainable system architectures.
• Acting as a catalyst for change, driving continuous improvement and modernisation across the engineering organisation.
• Being a strong proponent of Test-Driven Development (TDD) and shift-left practices to enable effective CI/CD pipelines and high-quality releases.

Generative AI & Intelligent Automation Responsibilities

• Architect and build production-grade Generative AI systems: Lead the hands-on development of LLM-powered solutions, AI-enabled services, and agentic frameworks that are performant, scalable, and deployed directly into commercial production environments to solve real business problems.
• Integrate Generative AI into core financial workflows: Design AI-driven capabilities that enhance analytics, automation, decision support, and operational efficiency within the BestX platform, while meeting strict performance, security, and regulatory requirements.
• Pioneer intelligent automation using agents: Design and implement autonomous and semi-autonomous agents capable of reasoning, planning, and orchestrating complex workflows across distributed systems to automate critical enterprise processes and reduce operational risk.
• Apply strong engineering discipline to AI systems: Ensure AI solutions adhere to the same high standards as core platform services, including observability, testing, versioning, explainability, security, and cost control.
• Collaborate across product, data, and business stakeholders: Translate business problems into well-architected AI solutions, balancing innovation with reliability and regulatory expectations.
• Shape AI engineering best practices: Contribute to standards and patterns for prompt management, model integration, evaluation, and lifecycle management within a regulated, enterprise-grade environment.