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Tier-1 brand, mid-level ML/AI role in metro with common skillset increases applicant competition.
Core ML, Python, and cloud skills are transferable, though financial services governance increases domain specificity.
Mandatory 5+ years plus specific ML, Python, AWS, and LLM framework requirements enforce strict filtering.
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Design, develop, and deploy scalable Generative AI, Agentic AI, Machine Learning, and RAG-based applications using Python and AWS.
Lead backend optimization, data integration efforts, and technical design discussions in AI/ML projects within the financial services domain.
Collaborate with business stakeholders and cross-functional teams to translate requirements into secure, scalable cloud-native AI solutions following enterprise security and governance standards.
Minimum 5 years of experience in software development, system integration, database design, and back-end architecture.
Bachelor’s degree in Computer Science or relevant field (B.E./B.Tech) or Master’s/Diploma in Computer Science.
Expert-level proficiency in Python, AWS Cloud Services, and building scalable enterprise/cloud-native applications.
Experience with Agentic AI, Generative AI technologies, RAG solutions, and at least one framework such as LangChain, LangGraph, Google ADK, CrewAI, or AutoGen; familiarity with prompt engineering, vector databases, and AI agent orchestration.
Experienced in leading end-to-end AI/ML solution architecture and implementation in cloud environments, specifically AWS.
Skilled at integrating advanced AI paradigms (Agentic AI, Generative AI, RAG) into production-grade systems within financial services or related sectors.
Capable of collaborating effectively with business leaders and cross-functional technical teams to drive strategic AI initiatives and ensure compliance with security and regulatory standards.