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GenAI Technical Architect

GenAI Technical Architect

Niit Technologies
10-18 Years
Early Applicant
  • Posted 23 hours ago
  • Be among the first 10 applicants

Job Description

Job Title - GenAI Architect

Skills - Python, Machine Learning, GenAI, AgenticAI, Large Language Models (LLMs), Azure OpenAI / AWS Bedrock / Vertex AI

Experience - 10 - 18 years

Locations - Greater Noida

Work Mode - 5 Days WFO

We at Coforge are hiring for GenAI Architect with the following skillset:

  • Design, develop, and deploy enterprise-scale Generative AI and AI/ML solutions.
  • Lead the development of AI systems leveraging Large Language Models (LLMs), Agentic AI frameworks, and cloud-native AI services.
  • Drive end-to-end ownership of AI/ML solutions from data preparation and model training to deployment and production support.
  • Build, customize, fine-tune, and optimize Large Language Models using Azure OpenAI, AWS Bedrock, Google Vertex AI, and other GenAI platforms.
  • Design and implement Retrieval Augmented Generation (RAG) frameworks, vector databases, embeddings, and prompt engineering strategies.
  • Perform data collection, data mining, preprocessing, and analysis of structured and unstructured datasets.
  • Develop scalable AI architectures leveraging cloud services, MLOps practices, and distributed computing frameworks.
  • Collaborate with business stakeholders, product teams, and engineering teams to translate business problems into AI-powered solutions.
  • Establish best practices around AI model governance, security, performance optimization, evaluation, and observability.
  • Mentor development teams on AI/ML technologies, modern Python practices, and Generative AI implementation patterns.

Looking forward to receiving your profile. For more details, please reach out to [Confidential Information].

More Info

Key Skills

GenAI

Generative AI

AWS Bedrock

Prompt engineering

LLMs

RAG frameworks

Vector databases

Azure OpenAI

Agentic AI

Embeddings

Distributed computing frameworks

Google Vertex AI

Retrieval Augmented Generation

Large Language Models

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