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Tier-1 brand, metro locations, and broad GenAI/full-stack requirements create high competition.
Requires specialized ML/GenAI and large financial services experience, making background transferability low and domain-sensitive.
Explicit 10+ years, deep GenAI/ML stack, cloud and enterprise finance experience imply very strict filters.
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Lead design and development of microservices and distributed AI/ML architectures leveraging foundational models and prompt engineering.
Own cloud-native deployment and orchestration of AI solutions using container technologies and public cloud platforms.
Drive enterprise-scale agile delivery within large financial services environments with stakeholder and executive communication.
At least 10 years of professional experience in microservices, AI/ML technologies, and distributed architectures.
Strong expertise in Python, Java, AI frameworks (PyTorch, TensorFlow, LangChain, Hugging Face), and foundational models (e.g., Gemini, OpenAI).
Experience with cloud platforms AWS, Azure, or GCP and cloud-native architectures.
Experience working in large-scale financial services enterprises.
Technical leader comfortable managing complex AI/ML projects with operational responsibilities including deployment and monitoring.
Experienced in enterprise agile frameworks (SAFe) and collaborating with diverse stakeholders across large organizations.
Skilled in integrating advanced AI technologies into scalable cloud environments supporting financial services use cases.