Senior Search Engineer

Essential functions

• Search Architecture: Design and implement high-performance indices with optimal structuring and mapping for diverse data types.

• System Optimization: Perform full-text search tuning using BM25 and other ranking algorithms to ensure precision and relevance.

• Hybrid Search Development: Build and maintain hybrid search systems that combine vector (semantic) and lexical search capabilities.

• Infrastructure Management: Scale distributed search systems to ensure high availability and robust performance.

• Security & Compliance: Implement search security protocols, including RBAC, TLS, and access control, while adhering to cloud-native privacy principles.

• Development & Integration: Write efficient code for data preparation, indexing, and API interaction, utilizing Docker and Kubernetes for automated deployment.

• Collaboration: Work closely with cross-functional teams to integrate AI agents into the broader eCommerce ecosystem and ML pipelines.

Qualifications

Total Professional Experience: 8+ years

Technical Skills

• Search Engines: Deep expertise in Elasticsearch, OpenSearch, or Vertex AI Search, including architecture, core principles, and DSL queries (aggregations and filters).

• Vector Search: Proven experience creating and optimizing vector embeddings and implementing hybrid search models.

• Cloud & DevOps: Strong hands-on experience with Google Cloud Platform (GCP), Docker, and Kubernetes.

• Programming: Ability to write clean, efficient code for data processing and API integration.

• CI/CD: Solid understanding of CI/CD principles specifically tailored to ML pipelines and search services.

Experience & Soft Skills

• AI Frameworks: Familiarity with AI agentic frameworks, LLM Observability, prompt engineering, and AgentOps.

• Architecture: Experience designing scalable, fault-tolerant AI architectures.

• Communication: Excellent interpersonal skills with the ability to collaborate effectively in a fast-paced, evolving environment.

• Tools: Knowledge of AI development environments, including visual IDEs, debugging tools, and testing frameworks.

Would be a plus

• Strong understanding of AI agentic frameworks, including concepts like LLM Observability, LLM models management, prompt engineering, AgentOps, and various agent frameworks.
• Expertise in designing scalable and fault-tolerant AI architectures.
• Experience with cloud-native security, privacy, and compliance principles.
• Familiarity with various AI agent complexity categories and their associated development efforts.
• Knowledge of tools and technologies used in AI development environments, including visual IDEs, debugging tools, and testing frameworks.
• Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams and stakeholders.
• Ability to work in a fast-paced and evolving environment.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• 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. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment 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.