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Tier-1 brand plus metro location and mid-level generalist demand increase competition despite niche agentic/LLM specialization.
Strong requirement for regulated finance experience and governance reduces cross-industry transferability.
Mandatory 5+ years, production ML, regulated finance experience and platform ownership imply high hiring filter strictness.
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Own the end-to-end onboarding lifecycle for AI/ML and LLM use cases on the finance agentic platform, ensuring production readiness in a regulated environment.
Define, prioritize, and drive the agentic framework roadmap aligned with product strategy to standardize reusable AI components and integration patterns.
Build and maintain high-quality Python platform components applying modern engineering practices and ensure operational stability, monitoring, and resilience of ML systems in production.
5+ years of professional experience delivering AI/ML solutions in production with end-to-end ownership.
Applied experience with agentic platforms or frameworks and knowledge of their operational and architectural considerations.
Advanced proficiency in Python and strong software engineering fundamentals including system design, testing, code review, and operational ownership.
Experience delivering AI/ML within financial services or similarly regulated industries with understanding of governance, risk, and control expectations for AI and data systems.
Experienced in collaborating cross-functionally as a technical anchor bridging product, decision science, and technology delivery teams in AI/ML contexts.
Practically skilled in applying LLM techniques such as prompt engineering, retrieval-augmented generation, fine-tuning, and agentic frameworks in production.
Able to define technical roadmaps, identify capability gaps, translate requirements with clear acceptance criteria, and communicate complex technical concepts confidently to senior stakeholders.