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Shivananda GolleSG

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À propos de Shivananda

Je conçois des systèmes RAG — des pipelines IA qui permettent à vos équipes de rechercher et interroger vos documents internes en langage naturel. Recherche vectorielle, graphes de connaissances, intégration de LLM, déployés sur AWS.
Actuellement chez Ericsson R&D, je développe un système Graph RAG en production sur plus de 36 000 entités. Stack : Python, LangChain, Neo4j, AWS (Bedrock, Neptune, Lambda), Docker.
Disponible depuis Paris pour des missions en IA, en remote ou hybride.
  • Anglais

    Capacité professionnelle complète

  • Français

    Notions

  • Télougou

    Bilingue ou natif

Accepte de travailler sur site
Paris (jusqu’à 50 km)

Expériences

  • Ericsson R&D
    AI Engineer Intern
    TÉLÉCOMMUNICATIONS
    mars 2026 - Aujourd'hui (3 mois)
    91300 Massy, France
    • • Built domain-specific Graph RAG systems for 3GPP telecom documents, combining vector embeddings with
    knowledge graphs (Neo4j, AWS Neptune) to enable structured retrieval over 36K+ entities and relations.
    • • Designed schema-guided extraction and structure-aware chunking strategies for LLM-based pipelines, improving entity precision and reducing noisy relations in large-scale document intelligence workflows.
    • • Evaluated multiple retrieval strategies (vector, graph, hybrid) across knowledge graph configurations, benchmarking retrieval quality and factual accuracy using automated evaluation frameworks.
    • • Optimized end-to-end pipeline infrastructure on AWS (S3, Lambda, Step Functions, EC2, ECR, IAM, Bedrock, Neptune), reducing LLM inference latency from 214s to 97s and cost by approximately 80%.
    Retrieval-Augmented Generation (RAG) Knowledge graph Claude Code Prompt engineering Cloud AWS
  • Infosys
    Systems Engineer
    CONSEIL & AUDIT
    novembre 2022 - janvier 2025 (2 ans et 2 mois)
    Hyderabad, Telangana, India
    • • Customized Finacle-based core banking solutions for enterprise clients, configuring business logic, transaction
    workflows, and product definitions using Finacle scripting and the ABCD customization tool.
    • • Built and maintained data processing pipelines using SQL and Python, improving data extraction and transformation
    efficiency by approximately 30% for downstream reporting and analytics.
    • • Worked across Linux-based development environments with Git for version control, supporting deployment workflows and environment configuration for banking application releases.
    Programmation Python MySQL Git Linux Customization

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Formations

  • Master of Science
    EPITA School of Engineering
    2026
    Master of Science
  • Bachelor of Technology
    Jawaharlal Nehru Technological University (JNTU)
    2022
    Bachelor of Technology

Compétences

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