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Tier-1 brand, mid-level ML/AI role in metro with broad GenAI skillset increases candidate competition.
Specialized agentic AI, LLM/RAG and Azure data platform skills reduce cross-industry transferability.
Mandates 3+ years, production agentic AI, Azure and LLM/RAG skills, implying strict technical filters.
Lead design and deployment of AI-enabled workflows and technical reporting automation within TAS, integrating with Shell’s enterprise data platforms.
Develop and manage agentic AI solutions including multiagent orchestration, diagnostics, and reporting to enhance process efficiency and cross-business insights.
Ensure compliance with AI governance, data quality standards, and security practices while driving continuous improvement in technical reporting.
Engineering degree in Computer Science or related technical field, or Any Engineering Degree with Post Graduate Degree/Diploma in Data Sciences.
Minimum 3+ years hands-on experience designing, building, and operating production grade agentic AI solutions with multiagent workflows, orchestration, and guardrails.
Strong hands-on experience with Azure data platforms (ADF, Databricks/Spark), data lakes, data modelling, and building reliable data pipelines integrated with enterprise data products.
Proficiency in Python (preferred) and/or Scala, SQL, API/service development, automation, and software engineering best practices including Git and CI/CD.
Experienced AI and data engineering professional capable of translating strategic digital initiatives into scalable, automated technical solutions within large asset management contexts.
Comfortable working with complex enterprise data ecosystems and implementing robust AI governance and compliance frameworks.
Skilled in end-to-end ownership of AI workflows including design, implementation, monitoring, and continuous optimization aligned with business objectives.