Principal/Senior Graph Solution Engineer

5 hours ago

Hyderabad, India Agivant Technologies Full time

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. (ref:hirist.tech)

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