Principal/Senior Graph Solution Engineer

1 day ago

Hyderabad, Telangana, India Agivant Technologies Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Requirements

  • Graph and Vector Data Science : Experience in applying graph algorithms, vector embeddings, and data science techniques for enterprise analytics.
  • SQL Expertise : Experience in SQL for querying, performance tuning, and debugging in relational and graph contexts.
  • Graph Databases and Platforms : Experience with Graph Database Products like Tigergraph, Neo4J, Janusgraph or similar systems, focusing on multi-modal graph + vector integrations.
  • Programming & Scripting : Experience in Python, C++, and automation tools for task management, issue resolution, and GSQL development.
  • HTTP/REST and APIs : Expertise in building and integrating RESTful services for database interactions.
  • Linux and Systems : Strong background in Linux administration, scripting (bash/Python), and distributed environments.
  • Kafka and Streaming : Experience with Kafka for real-time data ingestion and event-driven architectures.
  • Cloud Computing : Experience with AWS, Azure, or GCP for virtualization, deployments, and hybrid setups.
  • Graph Neural Networks (GNNs) and Graph Machine Learning : Hands-on with frameworks like PyTorch Geometric for predictive analytics on graphs.
  • Retrieval-Augmented Generation (RAG) and Semantic Search : Building pipelines with vector embeddings and LLMs for AI applications.
  • Multimodal Data Handling : Managing text, images, video in graph + vector setups.
  • Agile Methodologies and Tools : 3+ years with Scrum/Agile, JIRA, or Confluence.
  • Presentation and Technical Communication : Advanced whiteboarding, architecture reviews, and demos.
  • Cross-Functional Collaboration : Leading discovery, data modeling (UML, ER diagrams), and on-call incident to have Skills :
  • Data Governance, Security, and Compliance : Knowledge of encryption, access controls, GDPR/HIPAA, and ethical AI practices.
  • Big Data Processing Tools : Proficiency in Apache Spark, Hadoop, or Flink for distributed workloads.
  • AI-Driven Database Management and Optimization : Skills in AI-enhanced query optimization and performance tuning.
  • Monitoring & Observability Tools : 4+ years with Prometheus, Grafana, Datadog, or ELK Stack.
  • Networking & Load Balancing : Proficient in TCP/IP, load balancers (NGINX, HAProxy), and troubleshooting.
  • K8s (Kubernetes) : Proficiency in container orchestration for scalable deployments.
  • DevOps and CI/CD Pipelines : Advanced use of Git, Jenkins, or ArgoCD for automation.
  • Real-Time Analytics and Streaming Integration : Beyond Kafka, experience with Flink or Pulsar.

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