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Tier-1 brand, metro location, mid-level AI/ML role, and broad LLM/production requirements create high competition.
Strong finance/regulatory expectations increase domain bias, though ML/LLM engineering skills remain transferable.
Explicit 5+ years plus mandated LLM, agentic platform, Python, and regulated-finance experience increases filtering strictness.
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Own the end-to-end onboarding lifecycle of AI/ML and LLM use cases onto the finance agentic platform, ensuring production readiness in a regulated environment.
Define, prioritize, and drive the agentic framework roadmap to standardize integration patterns, evaluation metrics, and reusable AI components aligned with product strategy.
Build and maintain high-quality Python platform components using modern engineering practices and ensure operational stability, monitoring, and resilience of ML and agentic systems in production.
5+ years building and delivering AI/ML solutions in production with end-to-end ownership including operational stability.
Applied experience with agentic platforms or frameworks distinguishing agentic AI from conventional ML pipelines.
Advanced proficiency in Python with strong software engineering fundamentals (system design, testing, code reviews, operational ownership).
Experience delivering AI/ML solutions in a financial services or similarly regulated environment with governance, risk, and control considerations.
Experienced in cross-functional collaboration as a technical anchor bridging product, data science, and delivery teams within regulated financial services.
Skilled in applying advanced LLM techniques (prompt engineering, RAG, fine-tuning) for production-scale agentic AI systems.
Capable of managing technical roadmaps with a focus on measurable success metrics and delivering aligned AI platform outcomes under strict governance and responsible AI standards.