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Tier-1 brand, mid-level ML role, metro location and broad LLM+DevOps skillset increases candidate competition.
Core LLM and production ML skills transfer, but regulated banking context and controls increase domain sensitivity.
Explicit 4+ years, mandatory generative AI, LLM and production deployment skills enforce strict filters.
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Design, build, and operate production generative AI services using enterprise data and large language models to solve defined business problems with measurable outcomes.
Own end-to-end delivery from solution design, data preparation, evaluation, deployment, monitoring, to continuous improvement of AI solutions.
Develop and implement multi-step AI workflows with controls for safe execution and maintain automated build, test, and deployment pipelines including containerization on Kubernetes.
Bachelor's degree or equivalent in computer science, data science, engineering, statistics, or related quantitative field.
4+ years of hands-on experience using Python to build data-driven or machine learning-enabled production solutions.
Hands-on experience with generative AI applications using large language model APIs and multi-step agent AI workflows with hallucination and data leakage controls.
Proficiency in SQL with experience in MySQL, Oracle, or PostgreSQL and experience deploying containerized applications on Kubernetes.
Experienced in delivering scalable AI services with measurable business impact in production environments involving large language models.
Comfortable independently managing full solution lifecycle from design through monitoring, collaborating with cross-functional teams, and applying ML concepts including model evaluation and experimentation.
Skilled in automation and operational stability of AI workloads with observability, continuous integration/delivery, and cloud-native deployment practices.