Job Requirements At Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible.

Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future. We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster

We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.

Job Summary We are seeking a highly skilled Senior OpenSearch Engineer to design, build, and optimize next-generation search platforms for a large-scale eCommerce ecosystem.

The ideal candidate will possess deep expertise in OpenSearch/Elasticsearch, Vector

Search, Semantic Retrieval, Generative AI, Amazon Bedrock, and Retrieval

Augmented Generation (RAG). This role will focus on enhancing product discovery, search relevance, recommendations, conversational commerce, and AI-powered customer experiences.

The engineer will partner with Product, Data Science, Merchandising, and Engineering teams to deliver scalable search architectures that combine traditional keyword-based retrieval with contemporary semantic and GenAI-powered search capabilities.

Key Responsibilities Search Platform Engineering

- Design, deploy, and manage enterprise-scale OpenSearch clusters.
- Build high-performance search solutions for:
- Product Discovery
- Category Navigation
- Filtering & Faceted Search




- Autocomplete & Suggestions
- Product Recommendations
- Configure and maintain:
- Index Mappings
- Analyzers
- Tokenizers
- Synonym Dictionaries
- Ranking Models
- Optimize search relevance, latency, aggregations, and query performance.
- Build real-time and near-real-time indexing pipelines

Vector Search & Semantic Retrieval

- Design and implement vector-based retrieval systems.
- Develop semantic search capabilities using embedding models.
- Implement and optimize:
- Dense Vector Indexing
- k-NN Search
- Approximate Nearest Neighbor (ANN)
- Similarity Search
- Hybrid Search (Keyword + Vector)
- Build recommendation and personalization capabilities using embeddings.
- Define relevance benchmarks and evaluate semantic retrieval quality.

Generative AI & Amazon Bedrock

- Integrate OpenSearch with Amazon Bedrock services.
- Design and implement Retrieval-Augmented Generation (RAG) architectures.
- Build AI-powered use cases including:
- Natural Language Product Search
- Conversational Shopping Assistants
- AI Recommendations
- Intelligent Catalog Discovery
- Product Metadata Generation
- Work with:
- Amazon Titan Embeddings
- Cohere Embeddings
- Anthropic Claude
- Optimize embedding pipelines, chunking strategies, and retrieval accuracy.

Platform Operations & Reliability

- Monitor search clusters and indexing performance.
- Troubleshoot production incidents and search performance issues.
- Implement:
- Backup & Recovery
- Disaster Recovery
- Security Controls
- Capacity Planning
- Ensure high availability and platform scalability.





Cloud & DevOps

- Automate deployments using CI/CD pipelines.
- Implement Infrastructure as Code (IaC).
- Manage containerized search environments.
- Support cloud-native architectures on AWS.

We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace. Work Experience OpenSearch / Elasticsearch

- OpenSearch
- Elasticsearch
- Query DSL
- Search Relevance Tuning
- Aggregations
- Index Lifecycle Management
- Sharding & Replication
- Analyzers & Tokenizers
- OpenSearch Dashboards
- Kibana

Vector Search & AI Search

- Vector Databases
- Vector Indexing
- Embedding Generation
- Semantic Search
- Retrieval Systems
- Hybrid Search Architecture
- Similarity Ranking
- k-NN Search
- ANN Algorithms
- Embedding Lifecycle Management
- Retrieval-Augmented Generation (RAG)

Amazon Bedrock & Generative AI

- Amazon Bedrock
- Foundation Models
- Prompt Engineering
- Embedding Models
- Knowledge Bases
- Agentic AI Workflows
- Generative AI Applications
- Semantic Retrieval Systems

Programming Skills At least one or more:

- Java
- Python
- Node.js
- Go (Preferred)

Additional Skills

- REST APIs
- Microservices Architecture
- Distributed Systems
- Scalability Engineering

AWS Cloud Technologies

- Amazon OpenSearch Service
- Amazon Bedrock
- Lambda
- ECS
- EKS
- S3
- DynamoDB
- API Gateway

DevOps & Platform Engineering

- Docker
- Kubernetes
- CI/CD Pipelines
- Terraform
- CloudFormation
- Infrastructure Automation

📌 Senior OpenSearch Engineer (Bengaluru)
🏢 Quest Global
📍 Bengaluru