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GenAI Engineer (Recent Events) at NTT DATA

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

18 Feb, 26

Salary

0.0

Posted On

20 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, AI/ML Frameworks, LLM Development, Prompt Engineering, GenAI Application Design, Data Engineering, ETL Pipelines, API Integration, Data Modeling, LangChain, Vector Databases, RAG Techniques, Cloud Platforms, Containerization Tools, SQL, NoSQL Databases, Performance Tuning

Industry

IT Services and IT Consulting

Description

Develop and implement AI/GenAI components for prospect watchlist automation, including coding for LLM-based features and intelligent agents. Design and build data pipelines to ingest, clean, and transform data from internal systems and external APIs (e.g., CapIQ, Bankruptcy Data, Bloomberg). Collaborate with the Senior GenAI Engineer to optimize prompt engineering and integrate AI patterns into the solution architecture. Write production-grade code for AI workflows, including model orchestration, retrieval-augmented generation (RAG), and multi-agent systems. Implement API integrations and ensure data readiness for LLM-based insights and recommendations. Conduct model testing, fine-tuning, and performance optimization to meet accuracy and latency requirements. Document technical processes and contribute to best practices for AI development and data engineering. Strong proficiency in Python and experience with AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). Hands-on experience with LLM development, prompt engineering, and GenAI application design. Solid understanding of data engineering concepts, including ETL pipelines, API integration, and data modeling. Familiarity with LangChain, vector databases (e.g., Pinecone, Weaviate), and RAG techniques. Experience working with cloud platforms (Azure, AWS, or GCP) and containerization tools (Docker/Kubernetes). Ability to work collaboratively across distributed teams and deliver high-quality technical solutions under tight timelines. Exposure to enterprise-scale AI deployments and integration with CRM or ERP systems. Knowledge of SQL, NoSQL databases, and data governance best practices. Experience in performance tuning for LLMs and implementing scalable architectures.

Responsibilities

Develop and implement AI/GenAI components for prospect watchlist automation. Collaborate with the Senior GenAI Engineer to optimize prompt engineering and integrate AI patterns into the solution architecture.