ポジションについて
Job Summary
Job Description: AI Lead Engineer (Wealth Data Platform)
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 Lang Graph, ADK, CrewAI, or Auto Gen) 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 Sage Maker 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
Technical Requirements:
-
AI/ML Foundations: Deep expertise in LLM orchestration (RAG), Fine-tuning, and Prompt Engineering.
-
Graph Technology: Experience building Ontologies or using Graph-based RAG to improve the retrieval of structured/unstructured wealth data.
-
Data Stack: Proficiency in Python and SQL. Familiarity with Snowflake (Cortex), AWS Sage Maker, and Kafka for real-time agent triggers.
-
Engineering Rigor: Experience with LLMOps (monitoring, evaluation, and versioning) within a highly regulated Banking (FCA/PRA) environment.
✅ Mandatory YES/NO filters:
✅ Python + SQL (strong hands-on)
-
✅ LLM experience (RAG + Prompt Engineering)
-
✅ Built GenAI/LLM applications (real projects)
-
✅ Py Torch or Tensor Flow
-
✅ Data engineering exposure
-
✅ Cloud (AWS/Snowflake)
✅ Strong preference:
-
✅ Agentic AI frameworks
-
✅ Knowledge graph / Neo4j
-
✅ Kafka / real-time systems
-
✅ LLMOps / MLOps
-
✅ Banking / regulated domain
Other Requirements
null
福利厚生
•Learning Budget
HCL Technologiesについて
Bengaluru
本社所在地
