Job Summary

Offer SR for : Vishal Narula

Key Responsibilities

• Natural Language Democratisation: Develop and deploy Text-to-SQL and Text-to-Insight interfaces that allow non-technical Wealth Managers to interact with the conformed data layer using LLMs.
• Ontology & Knowledge Graph Engineering: Design and implement a domain-specific Wealth Ontology. Graph databases (e.g., Neo4j or Snowflake Relational Graphs) need to be leveraged to map complex client relationships and financial hierarchies that standard SQL fails to capture.
• Agentic Workflows: Build and orchestrate Autonomous Agents (using frameworks like LangGraph, ADK, CrewAI, or AutoGen) capable of executing multi-step financial reasoning such as automated portfolio rebalancing checks or proactive client insight generation.
• Modern Data Alignment: Ensure all AI models are integrated into the SageMaker Unified Studio and adhere to the bank’s OBDQ standards to prevent "hallucinations" in regulated client reporting.
• Productivity Tooling: Work with Analytics Engineers to embed LLM-based chatbots into front-line tools to reduce manual data gathering time for client-facing staff.

Key Responsibilities

Key Responsibilities

• Natural Language Democratisation: Develop and deploy Text-to-SQL and Text-to-Insight interfaces that allow non-technical Wealth Managers to interact with the conformed data layer using LLMs.
• Ontology & Knowledge Graph Engineering: Design and implement a domain-specific Wealth Ontology. Graph databases (e.g., Neo4j or Snowflake Relational Graphs) need to be leveraged to map complex client relationships and financial hierarchies that standard SQL fails to capture.
• Agentic Workflows: Build and orchestrate Autonomous Agents (using frameworks like LangGraph, ADK, CrewAI, or AutoGen) capable of executing multi-step financial reasoning such as automated portfolio rebalancing checks or proactive client insight generation.
• Modern Data Alignment: Ensure all AI models are integrated into the SageMaker Unified Studio and adhere to the bank’s OBDQ standards to prevent "hallucinations" in regulated client reporting.
• Productivity Tooling: Work with Analytics Engineers to embed LLM-based chatbots into front-line tools to reduce manual data gathering time for client-facing staff.

Skill Requirements

Key Responsibilities

• Natural Language Democratisation: Develop and deploy Text-to-SQL and Text-to-Insight interfaces that allow non-technical Wealth Managers to interact with the conformed data layer using LLMs.
• Ontology & Knowledge Graph Engineering: Design and implement a domain-specific Wealth Ontology. Graph databases (e.g., Neo4j or Snowflake Relational Graphs) need to be leveraged to map complex client relationships and financial hierarchies that standard SQL fails to capture.
• Agentic Workflows: Build and orchestrate Autonomous Agents (using frameworks like LangGraph, ADK, CrewAI, or AutoGen) capable of executing multi-step financial reasoning such as automated portfolio rebalancing checks or proactive client insight generation.
• Modern Data Alignment: Ensure all AI models are integrated into the SageMaker Unified Studio and adhere to the bank’s OBDQ standards to prevent "hallucinations" in regulated client reporting.
• Productivity Tooling: Work with Analytics Engineers to embed LLM-based chatbots into front-line tools to reduce manual data gathering time for client-facing staff.

Other Requirements