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Strong employer brand, mid-level GenAI role, and broad skillset requirements increase candidate competition.
GenAI engineering skills are transferable but enterprise integrations and regulated-data exposure increase domain sensitivity.
Explicit 5+ years, 2+ GenAI requirement, and mandatory LLM/vector DB skills increase shortlisting strictness.
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Build and support production-ready Generative AI solutions including RAG-based assistants and agentic workflows integrating with enterprise data and applications.
Translate solution designs into secure, scalable implementations with observability, reusable components, and strong engineering practices.
Implement and maintain AI services with enterprise integration, quality monitoring, and developer productivity enhancements.
5+ years total IT/software engineering experience including enterprise applications, APIs, and services.
2+ years hands-on experience with AI/ML/Generative AI solutions development or support.
Strong Python skills with the ability to build services, scripts, and automation.
Experience with LLMs, RAG frameworks (vector DB, retrieval, grounding), agentic AI patterns, and secure coding practices.
Experienced in developing scalable AI/ML solutions in enterprise or regulated environments, preferably with financial services exposure.
Demonstrates ownership in translating complex requirements into testable, reliable software with strong quality monitoring.
Comfortable working collaboratively with architects, product owners, and operations teams in structured engineering workflows.