Data Engineer Senior Consultant Job at NTT DATA, Inc., Indiana

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  • NTT DATA, Inc.
  • Indiana

Job Description

Req ID: 341149

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Data Engineer Senior Consultant to join our team in Pune, Mahārāshtra (IN-MH), India (IN).

Location: | Experience: 5+ years 
Role Overview
We’re hiring an AI Engineer to design, build, and productionize GenAI and agentic systems (RAG, tool-using agents, workflow/graph-based orchestration) on one or more hyperscalers (Azure, AWS, GCP). You’ll develop the full lifecycle—data/feature/RAG pipeline design, model selection/finetuning, safety/guardrails, evaluation/observability, and MLOps deployment.
Key Responsibilities
•    Build GenAI/agentic systems (chat copilots, workflow/graph agents, tool use, memory)
•    Implement chunking, hybrid search, vector stores, re-ranking, feedback loops, and continuous data quality/eval.
•    Select/integrate/finetune LLMs & multimodal models.
•    Apply prompt-engineering techniques to specific use cases and types
•    Experience working on solutions based on LLM, NLP, DL (Deep Learning), ML (Machine Learning), object detection / classification etc.
•    Should have good understanding of DevOps 
•    Should have good understanding of LLM evaluation
•    Should have deployed min of 2 models in production (MLOps)
•    Should have understanding of guardrails, policy filters, PII redaction, runtime monitors and agent observability.
•    Unit testing of GenAI Solutions built and documentation of results.
•    Collaborate with clients/Stakeholders from multiple Geographies.
•    Stay informed about the latest advancements in Gen AI, machine learning, and AI technologies to optimize our technical stack.
Qualifications
•    Bachelor’s/Master’s Degree or equivalent.
•    5+ years in ML engineering, around 1+ years of hands-on with LLMs/GenAI and agentic frameworks.
•    Experience in shipping production AI systems on at least one hyperscaler (Azure/AWS/GCP).
•    Experience delivering end-to-end GenAI based solutions.
Required Skills 
•    Strong Python experience to build multiple AI-ML/ GenAI Solutions. 
•    Should have experience working on Agent orchestration with leading frameworks like LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen. 
•    Strong experience working on SQL Query, Vector DB like Pinecone, Qdrant, Fiaas
•    Should have experience working on hybrid search and re-rankers 
•    Should have experience on evaluation & observability LangSmith/ human-in-the-loop workflows. 
•    Strong experience in using any one of the leading Hyperscaler services from Azure/AWS/GCP
•    Experience working on NLP, CV, Deep Learning Algorithms
•    Should have working experience with Open-Source Models
•    Experience on UI/UX will be added advantage. 

#GenAINTT

________________________________________
RESUME SELECTION Guidelines:
•    Delivered at least 2 GenAI/Agentic AI solutions for clients
•    Extensive experience of minimum 5+ years on Python
•    Delivered 3–5 successful client POCs/MVPs

#GenAINTT

About NTT DATA

NTT DATA is a $30+ billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world’s leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services.  Our consulting and industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is part of NTT Group, which invests over $3 billion each year in R&D.

Job Tags

Work experience placement,

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