GenAI Engineer - Database

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Offered From the posting source checked Jun 20, 2026

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

Not verified

Verification

Not verified

Salary

Not verified

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

GenAI Engineer - Database Pune, MH, India Company Description: Job Description: Role Summary We are seeking a Lead, GenAI Database Engineer to design, build, and scale next-generation AI-native data platforms that power Generative AI, Retrieval-Augmented Generation (RAG), and Knowledge Graph-driven applications. This role sits at the intersection of graph theory, vector search, relational data modeling, and AI systems , with a strong emphasis on hands-on technical leadership . You will be responsible for architecting and implementing multi-modal data ecosystems that combine Graph Databases, Vector Databases, and Relational Databases to enable explainable, scalable, and production-grade GenAI solutions. Key Responsibilities 1. GenAI Data Architecture & Platform Design Design and lead end-to-end GenAI data architectures supporting: Retrieval-Augmented Generation (RAG) Knowledge Graph-augmented LLMs (good to have) Hybrid semantic + symbolic reasoning systems Architect polyglot persistence strategies , determining where Graph, Vector, and Relational databases are used and how they interoperate. Establish data standards, schemas, indexing strategies, and performance benchmarks for AI-driven workloads. 2. Graph Database & Knowledge Graph (Hands-on) Own the design, development, and optimization of Knowledge Graphs for enterprise-scale use cases. Model complex domains using nodes, edges, properties, and ontologies . Implement advanced graph capabilities: Entity resolution and linking Schema and ontology design (RDF / OWL where applicable) Graph inference, traversal, and reasoning Hands-on experience with graph query languages . Engineer performant graph pipelines using databases. 3. Vector Databases & Semantic Retrieval Lead the implementation of vector-based retrieval systems to support semantic search and RAG pipelines. Design and manage: Embedding storage and lifecycle

Read the full description at jobs.smartrecruiters.com. FewerJobs shows a preview and links to the original posting.