Applix
Website:
applix.ai
Job details:
Job Summary
We are seeking an experienced Senior OpenSearch Engineer to design, develop, and optimize next-generation search solutions for our eCommerce platform. The ideal candidate will have deep expertise in OpenSearch/Elasticsearch, vector search, semantic retrieval, and Amazon Bedrock-powered Generative AI applications.
In this role, you will architect scalable search platforms that combine traditional keyword search with AI-driven semantic search, Retrieval-Augmented Generation (RAG), and recommendation systems to deliver intelligent product discovery, conversational commerce, and highly personalized customer experiences.
Key Responsibilities
Search Platform Engineering
- Design, deploy, and manage large-scale OpenSearch/Elasticsearch clusters in production environments.
- Build scalable and high-performance search capabilities for:
- Product Search
- Category Navigation
- Faceted Filtering
- Autocomplete & Typeahead
- Personalized Recommendations
- Design and maintain:
- Index mappings
- Custom analyzers
- Tokenizers
- Synonym dictionaries
- Relevance ranking models
- Optimize query performance, search relevance, aggregations, caching, and indexing throughput.
- Develop real-time and near real-time indexing pipelines for product catalogs, pricing, inventory, promotions, and customer data.
- Implement index lifecycle management (ILM), sharding, replication, and cluster optimization strategies.
Vector Search & Semantic Retrieval
- Design and implement vector-based search architectures using OpenSearch Vector Engine.
- Build semantic search solutions leveraging embedding models and vector representations.
- Configure and optimize:
- Dense Vector Indexes
- k-Nearest Neighbor (k-NN)
- Approximate Nearest Neighbor (ANN)
- Hybrid Search (Keyword + Vector)
- Similarity Search
- Develop AI-powered capabilities including:
- Semantic Product Search
- Similar Products
- Personalized Product Discovery
- Intelligent Recommendations
- Evaluate and continuously improve search quality using relevance metrics, semantic retrieval benchmarks, click analytics, and A/B testing.
Generative AI & Amazon Bedrock
- Design and implement Retrieval-Augmented Generation (RAG) solutions using Amazon Bedrock.
- Integrate OpenSearch with Amazon Bedrock Foundation Models for intelligent search experiences.
- Generate embeddings using supported models including:
- Amazon Titan Embeddings
- Cohere Embed
- Anthropic Claude
- Develop AI-powered use cases such as:
- Natural Language Product Search
- Conversational Shopping Assistants
- Product Recommendation Engines
- Catalog Enrichment
- Automated Metadata Generation
- Optimize embedding generation pipelines, document chunking strategies, vector storage, and retrieval performance.
- Collaborate with AI/ML teams to enhance semantic search relevance and GenAI capabilities.
Platform Operations & Reliability
- Monitor OpenSearch cluster health, indexing performance, query latency, and resource utilization.
- Troubleshoot production issues and perform root cause analysis.
- Implement high availability, backup, disaster recovery, and security best practices.
- Automate deployments using CI/CD pipelines and Infrastructure-as-Code (Terraform/CloudFormation).
- Conduct capacity planning and performance tuning for large-scale search workloads.
Cross-Functional Collaboration
- Work closely with Product Managers, Data Scientists, Merchandising, and Engineering teams to improve search relevance and customer experience.
- Partner with AI/ML teams to integrate embedding models and GenAI workflows.
- Drive best practices for enterprise search architecture, semantic retrieval, and AI-powered search solutions.
- Mentor junior engineers and contribute to technical design reviews and architecture discussions.
Required Skills
OpenSearch / Elasticsearch
- 5+ years of hands-on experience with OpenSearch and/or Elasticsearch.
- Strong expertise in:
- Query DSL
- Search Relevance Tuning
- Aggregations
- Index Lifecycle Management (ILM)
- Custom Analyzers & Tokenizers
- Synonyms
- Sharding & Replication
- Cluster Administration
- OpenSearch Dashboards / Kibana
Vector Search & Semantic Search
- Hands-on experience designing and implementing:
- Vector Indexing
- Embedding Pipelines
- Semantic Search
- Hybrid Search
- Retrieval Systems
- RAG Architectures
- Strong understanding of:
- k-NN Search
- ANN Algorithms
- Similarity Ranking
- Vector Embedding Lifecycle Management
- Search Evaluation Metrics
Amazon Bedrock & Generative AI
- Hands-on experience with Amazon Bedrock services and APIs.
- Strong understanding of:
- Foundation Models (FMs)
- Prompt Engineering
- Embedding Models
- Knowledge Bases
- Agentic AI Workflows
- Experience integrating Bedrock with OpenSearch for semantic retrieval and AI-powered search applications.
Programming & Software Development
Strong programming experience in one or more of the following:
- Java
- Python
- Node.js
- Go (Preferred)
Additional experience with:
- REST APIs
- Microservices Architecture
- Distributed Systems
- Performance Optimization
- Event-Driven Architectures
Cloud & DevOps
Experience with AWS services including:
- Amazon OpenSearch Service
- Amazon Bedrock
- AWS Lambda
- ECS / EKS
- DynamoDB
- Amazon S3
- API Gateway
Additional expertise in:
- Docker
- Kubernetes
- CI/CD Pipelines
- Terraform
- AWS CloudFormation
- Monitoring & Observability Tools
eCommerce Domain Expertise
Experience working on enterprise eCommerce platforms with knowledge of:
- Product Catalog Search
- Merchandising Search
- Faceted Navigation
- Personalized Recommendations
- Semantic Product Discovery
- Conversational Commerce
- Search Analytics
- Conversion Rate Optimization
- Product Ranking & Relevance
Preferred Qualifications
- Experience with Large Language Models (LLMs) and enterprise AI search implementations.
- Hands-on experience with Retrieval-Augmented Generation (RAG) frameworks such as LangChain or LlamaIndex.
- Knowledge of vector databases and embedding optimization techniques.
- Experience building scalable search platforms supporting millions of products and high search volumes.
- AWS certifications (Solutions Architect, Machine Learning, or Developer) are an added advantage.
- Strong analytical, problem-solving, and communication skills with the ability to work in Agile environments.
Why Join Us?
- Build next-generation AI-powered search experiences for large-scale eCommerce platforms.
- Work with cutting-edge technologies including OpenSearch, Amazon Bedrock, Vector Search, and Generative AI.
- Collaborate with highly skilled engineering and AI teams on enterprise-scale digital commerce solutions.
- Opportunity to shape intelligent search architectures that directly impact customer experience and business growth.
Click on Apply to know more.
