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piyushgaur373

Piyush G

@piyushgaur373

Software Engineer

India
Inglés
Parte de la información aparece en idioma inglés.
Sobre mí
I’m a backend-focused Software Engineer with 3+ years of experience building scalable systems at InfoEdge. I design and evolve search and data platforms that handle complex filtering and large-scale aggregations, integrating LLM-driven agents into Elasticsearch-based systems to optimize performance.... Lee más

Habilidades

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piyushgaur373
Piyush G
desconectado • 
Tiempo medio de respuesta: 2 horas

Revisa mis servicios

Aplicaciones Full Stack Web
I will build scalable backend apis
Sitios web y software con IA
I will build ai agents and workflow automation

Experiencia laboral

Infosys

Senior Software Engineer

Infosys • Tiempo completo

Aug 2023 - Present2 yrs 9 mos

Designed and built an AI-assisted, Elasticsearch-based search platform from scratch with a generic advanced query builder supporting hard/soft/range filters, significantly reducing manual ES query authoring effort across the team. • Implemented backend-driven, fully configurable filters (non-dynamic + saved searches) allowing recruiters to persist and resume complex search flows, enhancing workflow continuity and overall recruiter productivity. • Leveraged prompt engineering and context management to abstract raw Elasticsearch DSL complexity—new filters can be added or removed via standardized prompts, enabling even non-Elasticsearch experts to safely extend search capabilities. • Developed a Candidate Manager funnel view with filtered aggregation facets, where each filter dynamically recomputes option counts based on other selections, enabling precise end-to-end hiring pipeline tracking while optimizing query performance and bandwidth usage. • Migrated a legacy chat UI tool used by multiple InfoEdge verticals to a Dockerized architecture, configured Dockerfiles and Docker Compose, and deployed in a production environment to enable centralized usage and improve business performance. • Architected and implemented a dynamic, fault-tolerant Airflow pipeline to compute weighted, category-specific profile scores for 400K+ DAUs, leveraging ClickHouse for OLAP processing and S3 for stateful recovery