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GenAI Architect 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

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, AI, LLM, Prompt Engineering, Data Ingestion, API Integration, Cloud Platforms, Docker, Kubernetes, LangChain, Hugging Face Transformers, Vector Databases, Performance Tuning, Model Optimization, Security, Compliance

Industry

IT Services and IT Consulting

Description

Architect and implement GenAI solutions for enterprise-scale automation, including prospect research and watchlist creation. Hands-on coding and development of AI/LLM-based applications using Python and modern AI frameworks (e.g., PyTorch, TensorFlow, LangChain). Design and enforce architecture patterns for scalable, secure, and high-performance AI systems. Develop and optimize prompt engineering strategies for LLMs to enable accurate and context-aware outputs. Build agentic AI workflows for data ingestion, processing, and intelligent automation. Collaborate with data engineers and solution architects to ensure seamless integration of external APIs and internal data sources. Drive performance tuning and model optimization for GenAI components. Provide technical leadership and mentorship to offshore development teams. Expert-level proficiency in AI/ML programming with strong Python skills and experience in building production-grade AI systems. Deep knowledge of LLM architectures, prompt engineering, and agent frameworks. Proven experience in solution architecture for AI/GenAI platforms, including integration with enterprise data ecosystems. Hands-on experience with API integration, data pipelines, and distributed systems. Familiarity with cloud platforms (Azure, AWS, or GCP) and containerization (Docker/Kubernetes). Strong problem-solving skills and ability to work independently on complex technical challenges. Experience with LangChain, Hugging Face Transformers, and vector databases (e.g., Pinecone, Weaviate). Knowledge of retrieval-augmented generation (RAG) and multi-agent orchestration. Prior experience in enterprise AI deployments with strict security and compliance requirements.

Responsibilities

Architect and implement GenAI solutions for enterprise-scale automation. Collaborate with data engineers and solution architects to ensure seamless integration of external APIs and internal data sources.