Data / Retrieval Engineer

NTT DATA North America; Hyderabad; Hybrid; INR 2,500,000 - 4,200,000; Full time

Job summary

NTT DATA North America in Hyderabad, Telangana seeks a Senior Data/Retrieval Engineer to design, build and operate enterprise-grade data ingestion and retrieval capabilities for AI agents and knowledge-search platforms.

The role focuses on turning enterprise knowledge into secure, citation-backed context while enhancing retrieval quality, grounding, data readiness, latency and cost across Retrieval-Augmented Generation solutions.

Qualifications

• 7+ years of experience in data engineering, backend engineering, search engineering, machine learning engineering or knowledge-platform development.
• Strong hands-on experience with Python and SQL.
• Production experience implementing Retrieval-Augmented Generation or enterprise-search solutions.

Responsibilities

• Own the data ingestion and retrieval ecosystem supporting enterprise AI agents.
• Design and build scalable ingestion pipelines for structured, semi-structured and unstructured data.
• Develop indexing solutions using vector retrieval, keyword search, hybrid retrieval and semantic search.
• Implement document chunking, embedding generation, metadata enrichment and indexing strategies.
• Build reranking, grounding and citation-generation mechanisms to improve response accuracy and traceability.
• Convert business documents and knowledge assets into reliable, contextual and reusable data products.
• Implement access-aware retrieval based on users, roles, entitlements and source-system permissions.
• Apply metadata filtering, document lineage, freshness controls and source-level traceability.
• Establish controls for PII, sensitive data, data retention and governance evidence.
• Partner with AI-agent, MCP, application and platform engineers to improve retrieval relevance and cost.
• Create retrieval evaluation datasets with queries and relevance labels.
• Define and monitor retrieval-quality metrics and governance evidence.
• Develop monitoring dashboards, alerts and runbooks for retrieval quality and data freshness.

Skills

Python

SQL

Retrieval-Augmented Generation

Vector databases

Enterprise search

Problem solving

Education

Bachelor's in CS/Engineering

Tools

ElasticSearch

Job description

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,

We are currently seeking a Data / Retrieval Engineer to join our team in Hyderabad, Telangana (IN-TG), India (IN).

Job Description

Position: Senior Individual Contributor

Experience: 7+ years

Domain: RAG, Enterprise Search, Data Readiness and Retrieval Quality

Openings: 1

Role Overview

We are seeking an experienced Data / Retrieval Engineer to design, build and operate enterprise-grade data ingestion and retrieval capabilities for AI agents and knowledge-search platforms.

The role will focus on transforming enterprise business knowledge into secure, trustworthy and citation-backed context. The engineer will be responsible for improving retrieval quality, grounding, data readiness, latency and operational cost across Retrieval-Augmented Generation and enterprise-search solutions.

Key Responsibilities

• Own the data ingestion and retrieval ecosystem supporting enterprise AI agents.
• Design and build scalable ingestion pipelines for structured, semi-structured and unstructured data.
• Develop indexing solutions using:
• Vector retrieval
• Keyword search
• Hybrid retrieval
• Semantic search
• Implement document chunking, embedding generation, metadata enrichment and indexing strategies.
• Build reranking, grounding and citation-generation mechanisms to improve response accuracy and traceability.
• Convert business documents and knowledge assets into reliable, contextual and reusable data products.
• Implement access-aware retrieval based on users, roles, entitlements and source-system permissions.
• Apply metadata filtering, document lineage, freshness controls and source-level traceability.
• Establish appropriate controls for:
• Personally Identifiable Information
• Sensitive and confidential data
• Data retention
• Security and governance evidence
• Partner with AI-agent, MCP, application and platform engineers to improve retrieval relevance, grounding, latency and infrastructure cost.
• Create retrieval evaluation datasets, including representative queries, expected sources and relevance labels.
• Define and monitor retrieval-quality metrics such as Recall@K, Precision@K, Mean Reciprocal Rank, NDCG, citation accuracy and groundedness.
• Develop monitoring dashboards, alerts and operational runbooks for retrieval quality, data freshness and model or index drift.
• Troubleshoot production issues related to ingestion failures, missing documents, stale indexes, access-control leakage and poor retrieval relevance.
• Optimise retrieval pipelines for scalability, availability, observability and performance.

Required Skills And Experience

• 7+ years of experience in data engineering, backend engineering, search engineering, machine learning engineering or knowledge-platform development.
• Strong hands‑on experience with Python and SQL.
• Production experience implementing Retrieval-Augmented Generation or enterprise-search solutions.
• Strong understanding of:
• Vector databases
• Enterprise-search platforms
• Embedding models
• Chunking strategies
• Keyword and semantic search
• Hybrid retrieval
• Reranking
• Metadata management
• Experience building data pipelines, APIs and indexing workflows.
• Knowledge of relational databases, document databases or knowledge-retrieval platforms.
• Experience implementing role‑based or attribute‑based access controls within retrieval systems.
• Strong understanding of data security, privacy, lineage and governance.
• Experience with monitoring, logging, tracing and production observability.
• Ability to work with business, data, AI, security and platform‑engineering stakeholders.
• Strong analytical, problem-solving and communication skills.

Preferred Skills

• Experience with large‑scale enterprise knowledge bases and multi‑source document ingestion.
• Exposure to MCP‑enabled applications or agentic AI platforms.
• Experience with document parsing, OCR, table extraction and content normalisation.
• Knowledge of search relevance tuning and learning‑to‑rank techniques.
• Experience with cloud‑based data and AI platforms.
• Familiarity with financial‑services data, regulatory content or S&P‑related business information.
• Experience designing governance evidence, audit trails and data‑quality controls.

Indicative Technology Exposure

Programming and Data: Python, SQL, APIs, ETL/ELT pipelines

AI and Retrieval: RAG, embeddings, vector search, hybrid search, reranking, grounding, citations

Data Platforms: Vector databases, relational databases, document stores

Search: Enterprise search, keyword search, semantic search, metadata filtering

Governance: Data lineage, access controls, PII management, freshness and retention controls

Operations: Monitoring, logging, observability, quality evaluation and drift detection

Key Success Measures

• Improved retrieval relevance and citation accuracy.
• Reduced hallucination through stronger grounding.
• Reliable enforcement of document and user access permissions.
• Improved freshness and completeness of indexed enterprise data.
• Lower retrieval latency and infrastructure cost.
• Effective identification and remediation of retrieval‑quality drift.
• Production‑ready monitoring, governance evidence and operational runbooks.

Candidate Red Flags

• Experience limited to prompt engineering without hands‑on retrieval implementation.
• No experience evaluating retrieval relevance or grounding quality.
• Limited understanding of data pipelines, metadata or indexing.
• Weak knowledge of security, access control or sensitive‑data handling.
• Proof‑of‑concept experience without production deployment, monitoring or operational ownership.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in‑office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees.

NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com and @talent.nttdataservices.com email addresses.

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