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Metro location and visible AI title increase competition, balanced by seniority and niche generative AI requirements.
Regulatory, governance, and enterprise AI requirements increase industry specificity and reduce transferability.
Requires mandatory generative AI, Azure, DevSecOps, and regulated-environment experience, making filters stringent.
Design, build, deploy, and optimise AI-powered solutions (including RAG and vector search pipelines) within a regulated financial services environment.
Ensure high standards in code quality, system performance, observability, compliance, and responsible AI governance across AI applications.
Collaborate across cross-functional and international teams to deliver scalable AI capabilities that improve customer outcomes and operational efficiency.
Strong software engineering experience in Python (or similar languages) with hands-on expertise in generative AI technologies (LLMs, prompt engineering, embeddings, vector search, RAG).
Proven experience delivering production-grade AI and machine learning solutions in enterprise-scale, regulated environments (financial services preferred).
Working knowledge of cloud platforms (preferably Microsoft Azure), containerisation (Docker, Kubernetes), CI/CD pipelines, AI observability and governance tools.
Educational Qualification: Bachelor’s degree in any discipline. Work Experience Required: Proven experience in AI solution delivery; exact years not explicitly mentioned.
Experienced in regulated and compliance-sensitive financial or asset management environments with strong governance and security focus.
Demonstrates technical leadership in AI engineering best practices, mentorship, and continuous improvement in agile, fast-paced settings.
Hands-on expertise in generative AI frameworks and platforms with a balance of software engineering rigor and responsible AI governance mindset.