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Mid-level AI role, metro location, and broad, popular LLM skillset drive high candidate competition.
Core ML/LLM skills transfer across industries, though enterprise data and finance domain experience is preferred.
Mandatory 6+ years plus specialized LLM, cloud, and enterprise data requirements make shortlisting highly strict.
Lead design, development, and deployment of enterprise-grade AI solutions utilizing Large Language Models, Agentic AI, and Retrieval Augmented Generation techniques.
Build scalable AI-assisted applications including AI assistants, copilots, and multi-agent workflows to enhance software development, customer support, and operational efficiency.
Collaborate with cross-functional teams to identify AI use cases, evaluate emerging models/technologies, and establish best practices for prompt engineering, governance, and responsible AI adoption.
Bachelor's or Master's degree in Computer Science, Software Engineering, AI, Data Science, or related field.
6+ years of professional software engineering experience with hands-on delivery of enterprise AI solutions.
Proven expertise in Generative AI, LLM integration, Retrieval Augmented Generation (RAG), AI Agents, and cloud-native application development.
Experience with Python programming, SQL, REST APIs, and either Java or .NET; familiarity with enterprise data platforms (Databricks, Spark, AWS) is a significant advantage.
Experienced in architecting and deploying AI-powered applications in enterprise environments, especially leveraging modern AI frameworks (LangChain, Hugging Face, MCP).
Strong background in cloud-native, scalable microservices and data platform integration with understanding of distributed systems and modern data lakehouse architectures.
Capable of providing technical leadership and collaborating across product, engineering, and data teams to drive AI strategy and governance in regulated, complex financial services contexts.