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Global brand, metro location, mid-level generalist ML role, and broad skill requirements make competition high.
ML/AI skills are transferable across industries, but finance-specific compliance and domain knowledge raise specificity.
Explicit 3–5 year requirement plus mandatory ML/NLP, cloud, and CI/CD skills increase filtering strictness.
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Build and validate multi-agent AI workflows using frameworks like LangGraph, Cortex, and AgentCore to solve complex financial problems.
Develop evaluation frameworks and datasets to measure AI generative output performance, faithfulness, and accuracy.
Collaborate with engineers and investment professionals to integrate AI models into business workflows, ensuring compliance and reliability in financial services.
3-5 years of experience in data science or machine learning with focus on NLP and Generative AI.
Strong proficiency in Python and cloud-native development including Docker and CI/CD.
Experience or interest in LangGraph, LangChain, Copilot Studio, or AgentCore frameworks.
Workplace requirement: Hybrid model with at least three days a week in Hyderabad office.
Experienced in architecting and shipping intelligent AI systems rapidly, including evaluation and testing within business workflows.
Skilled at bridging data engineering and full stack development with agility to adapt based on sprint feedback.
Comfortable leveraging AI-assisted coding tools (GitHub Copilot, Cursor) to accelerate development and exploration.