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Senior, niche ML/AI role at a Tier-1 bank reduces applicant density, yielding medium competition.
Role requires specialized AI/MLOps, RAG and regulated financial-services governance, so background fit sensitivity is high.
Explicit 10–15 years, 3–5 years AI experience plus strict MLOps/governance requirements imply high shortlisting strictness.
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Design, engineer, and operationalize scalable AI orchestration frameworks integrating multiple AI models, agents, and enterprise applications to automate complex analytical and operational processes.
Develop enterprise-grade data products, scalable data pipelines, RAG architectures, and reusable AI platform components to support AI-enabled business capabilities.
Implement MLOps/LLMOps, Responsible AI guardrails, and AI observability solutions ensuring secure, auditable, and compliant AI operations within a regulated financial environment.
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Artificial Intelligence, or equivalent practical experience.
10-15 years of experience in Data Engineering, Machine Learning Engineering, Software Engineering, or related disciplines.
3-5 years of experience specifically in AI Engineering, including expertise in Prompt Engineering, Generative AI, Agentic AI, MCP Framework, or RAG Architecture.
Strong expertise in building large-scale data pipelines, distributed data processing solutions, Python, SQL, APIs, workflow automation, and cloud-native architectures.
Experienced professional capable of leading end-to-end design and deployment of complex, multi-agent AI orchestration systems in a financial services context.
Strong data engineering and AI engineering background with hands-on skills in building scalable, reusable AI and data products.
Proficient in governance, compliance, and risk management for AI solutions ensuring responsible AI practices within regulated environments.