Search Engineer

Grid Dynamics

United States

On-site

USD 100,000 - 130,000

Full time

14 days+

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Benefits offered by this job

Budget for conferences and courses

Well-equipped office

Corporate social events

Job summary

A technology consulting firm is seeking a hands-on Search Engineer to design and optimize large-scale search platforms. The role requires expertise in Solr or Elasticsearch, with responsibilities ranging from developing Java services to implementing machine-learning-driven search features. Candidates should have 5+ years of experience in back-end system development, as well as a strong understanding of search concepts and data pipeline construction. This position offers opportunities for growth and collaboration within a dedicated team.

Qualifications

5+ years building back-end systems in Java with a focus on performance.
3+ years hands-on with Apache Solr or Elasticsearch.
Proven track record delivering search features at scale.

Responsibilities

Own the full lifecycle of Solr/Elasticsearch clusters.
Develop high-throughput Java services exposing search functionality.
Prototype and productionize features like autocomplete and spell-checking.

Skills

Java

Apache Solr

Elasticsearch

Python

Docker/Kubernetes

Tools

Spring Boot

CI/CD

AWS

Job description

Overview

We’re looking for a hands-on Search Engineer to design, build, and optimize large-scale search platforms that power rich content and product discovery experiences. You will be our in-house expert on Solr or Elasticsearch, drive relevance and performance improvements, and collaborate with data scientists on machine-learning-driven ranking and agentic search features for multiple client projects. We are looking for E-Commerce or content search experience to support our search implementations in retail and general search domain.

Key Responsibilities

Search Platform Engineering

Own the full lifecycle of Solr/Elasticsearch clusters: schema design, index pipelines, scaling & monitoring.
Develop high-throughput, low-latency Java services that expose search functionality via REST / gRPC APIs.

Feature Development

Prototype and productionize features like faceted navigation, autocomplete/type-ahead, spell-checking, vector or hybrid search.
Integrate agentic or conversational layers to enable natural-language and multi-turn search use cases.
Partner with ML engineers to deploy PyTorch-based ranking models (query understanding, embeddings, re-ranking).
Build data pipelines (Python/Java/Spark/Dataflow) to generate training signals from user behavior logs.
Connect with Conversational Agents

Quality & Reliability

Instrument metrics, alerting, and automated tests to guarantee SLA compliance.
Lead performance profiling and capacity planning for indexes serving tens of millions of documents or SKUs.

Required Qualifications

5+ years building back-end systems in Java (Spring Boot or similar) with a focus on performance and scalability.
3+ years hands-on with Apache Solr or Elasticsearch (index design, relevance tuning, cluster operations).
Proven track record delivering content or product search features at scale (e-commerce, media, SaaS, or similar).
Solid understanding of IR concepts (tokenization, analyzers, BM25, vector search basics).
Proficiency in Python for data manipulation and prototyping.
Familiarity with Linux, Docker/Kubernetes, CI/CD, and cloud deployment (AWS, GCP, or Azure).

Preferred / Bonus Skills

Experience embedding or serving PyTorch models for LTR, embeddings, or generative re-ranking.
Exposure to agentic architectures (e.g., orchestrating multi-agent workflows, vector-store-backed retrieval for LLMs).
Knowledge of vector databases (OpenSearch/ES K-NN, Milvus, Pinecone, Weaviate, etc.).
Experience with streaming data pipelines (Kafka, Pub/Sub, Flink) for real-time indexing.
Contributions to open-source IR/ML projects or published technical talks/blogs.
Experience with modern search SaaS solutions like Algolia, Constructor.io or Vertex AI Search

Soft Skills

Pragmatic problem-solver who balances quick wins with long-term architecture.
Comfortable explaining trade-offs to product owners and mentoring junior engineers.
Passion for staying current with search, ML, and AI agent trends.

What We Offer

Impact: Own the search stack that directly shapes end-user experience.
Growth: Budget for conferences, courses, and dedicated R&D time.
Modern tech: Cloud-native, CI/CD, and the freedom to propose new tools.
Culture: Collaborative, engineering-led team that values knowledge sharing. Big internal search community
Opportunity to work on cutting-edge projects
Work with a highly motivated and dedicated team
Corporate social events
Well-equipped office

About us:

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. We solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. Grid Dynamics has 8 years of experience and leadership in enterprise AI, supported by expertise in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.

Seniority level