HCL Technologies
HCL Technologies

Lead Consultant(Development)

職種コンサル
経験リード級
勤務地Bengaluru, India
勤務オンサイト
雇用正社員
掲載1週間前
応募する

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

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Learning Budget

HCL Technologiesについて

Bengaluru

本社所在地