Senior OpenSearch Engineer

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 modern 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

Work arrangement
No