Location : Hyderabad (Work from Office/Hybrid)

Experience : 5 to 9 Years

Employment Type : Full-Time

Job Summary :

We are looking for an experienced Semantic Search & Elastic Engineer to design, develop, and optimize enterprise search platforms using Elasticsearch, Semantic Search, and AI-driven relevancy algorithms. The ideal candidate should have strong expertise in Elasticsearch administration, search optimization, vector search, and programming in Python or Java to build scalable and intelligent search solutions.

Key Responsibilities :

- Design, deploy, and maintain highly available self-managed Elasticsearch clusters.

- Configure cluster architecture including node management, replication, sharding, indexing, and performance optimization.

- Implement backup, restore, disaster recovery, and index lifecycle management strategies.

- Develop and optimize semantic search capabilities using AI/ML models such as BERT, ELSER (Elastic Learned Sparse Encoder), or transformer-based models.

- Design and implement vector search, hybrid search, and retrieval-augmented search solutions.

- Improve search relevancy using ranking algorithms, boosting strategies, synonym handling, analyzers, and role-based indexing.

- Develop search APIs and backend services using Python or Java.

- Integrate Elasticsearch with enterprise applications, knowledge management platforms, and AI solutions.

- Monitor cluster health, performance, and scalability using observability and monitoring tools.

- Troubleshoot indexing, query performance, and cluster issues.

- Work closely with Data Engineering, AI/ML, and Product teams to deliver intelligent search experiences.

- Follow DevOps best practices for deployment, automation, and infrastructure management.

Required Technical Skills :

- Strong hands-on experience with Elasticsearch/OpenSearch.

- Experience in Elasticsearch cluster administration and performance tuning.

- Strong understanding of :

1. Indexing

2. Sharding

3. Replication

4. Mapping

5. Analyzers

6. Aggregations

7. Query DSL

- Experience with Semantic Search and Relevancy Engineering.

- Knowledge of :

1. Vector Search

2. Dense/Sparse Embeddings

3. Hybrid Search

4. BM25

5. Learning-to-Rank (LTR)

- Hands-on experience with AI/ML models such as :

1. BERT

2. ELSER

3. Sentence Transformers

4. Embedding Models

- Strong programming skills in Python or Java.

- Experience building REST APIs and search services.

- Familiarity with Git and CI/CD pipelines.

Preferred Skills :

- Experience with Elastic Stack (ELK) :

1. Kibana

2. Logstash

3. Beats

- Experience with Docker and Kubernetes.

- Exposure to cloud platforms (AWS, Azure, or GCP).

- Knowledge of observability and monitoring tools.

- Experience integrating enterprise knowledge management platforms.

- Understanding of Generative AI, RAG (Retrieval-Augmented Generation), and LLM-based search is an added advantage.

Roles & Responsibilities :

- Architect scalable Elasticsearch infrastructure.

- Configure and optimize search indices for high performance.

- Develop semantic search solutions using AI-powered ranking models.

- Improve search accuracy through relevancy tuning and boosting techniques.

- Implement secure, role-based indexing and search access.

- Perform backup, recovery, and disaster recovery planning.

- Monitor cluster performance and resolve production issues.

- Collaborate with cross-functional teams to enhance enterprise search capabilities.

- Maintain technical documentation and follow best engineering practices.

Required Experience :

- 5 to 9 years of software engineering experience.

- Minimum 3+ years of hands-on Elasticsearch experience.

- Experience with Semantic Search, AI-based search relevance, or enterprise search platforms.

- Experience developing applications using Python or Java.

- Strong analytical and problem-solving skills.