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Strong brand, mid-level generalist title, metro location, and AI focus increase competition.
Requires ML production skills plus deep financial domain expertise, limiting cross-industry transferability.
Explicit years, required AI/ML production experience and specific tech stack create strict filters.
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Develop and deploy machine learning and AI solutions specifically for financial data applications, including working with Knowledge Graphs and NLP models.
Maintain and optimize AWS cloud infrastructure to support scalable, high-performance AI and ML solution delivery, including integration of large language models (LLMs).
Manage the entire software development lifecycle for financial AI applications, including data pipeline development for complex structured and unstructured financial data.
B.Tech/BE/M.Tech/ME in Computer Science or equivalent from a reputed college/university.
Minimum 2+ years of software engineering experience, with significant experience integrating AI/ML solutions in production environments.
Proficiency in Python, Docker, API development, AWS cloud architecture, and familiarity with SQL, NoSQL, and Vector databases.
Experience with event-driven architectures and working knowledge of ML/NLP concepts; strong communication skills bridging technical and business audiences.
Experience with Knowledge Graphs and applying NLP/ML in financial domain solutions, demonstrating domain-specific expertise.
Operating style includes strategic deployment and integration of diverse ML models in production, indicating senior software engineering responsibility.
Comfortable working cross-functionally with data scientists and ML engineers towards scalable, reliable AI applications in a financial enterprise environment.