HCLTech—Senior Technical Specialist

Job description

Description: 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