Prometheus, Kubernetes, OpenTelemetry, Go, Infrastructure-as-code

Java, Graphql, Scala, Kafka, TigerGraph, MLops, Docker, Neo4j, XGBoost, Spark, Kubernetes, Python, AWS, Airflow, pgvector, Qdrant, LightGBM, Go, MLflow, Flink, Neptune, Kubeflow, Milvus

Websocket, Kafka, Rtp, Gcp, Cti, Python, Golang, CCaaS, event-driven systems, AI ML pipelines, NATS, RAG, Redpanda, SIP

MongoDB, Rtp, Java, concurrency, Postgres, Sentry, Kafka, Datadog, System Design, Distributed Systems, AWS, Redis, Webrtc, Python, Kubernetes, Docker, Gcp, scalable high-availability APIs, Pub Sub, SIP, streaming systems

Hadoop, Kafka, Tensorflow, Pytorch, Gcp, Docker, Spark, Azure, Kubernetes, Python, AWS, Performance Optimization, Infrastructure as Code, AI ML Technologies, MLflow, TensorBoard, CI CD, Hybrid Cloud Architecture, Kubeflow

testing practices , architectural patterns , System Design, Coding Standards, Software Development, Distributed Systems, Apis, semantic search, GraphRAG, ontologies, schema governance, AI-enabled platform capabilities, integration solutions, evidence-based reasoning, AI-driven systems, semantic models, Retrieval pipelines, embeddings, RAG, versioning practices, hybrid search, taxonomies, knowledge graphs, knowledge bases, Knowledge Representation, data systems, Data Validation

Python Programming, Java, Rest Apis, Gcp, Git, Spring Boot, Elk, Distributed Systems, Datadog, AWS, Prometheus, Kubernetes, Azure, Docker, Jenkins, Hallucination and drift monitoring, Kafka streaming systems, PII PCI compliance, AI observability concepts, OpenTelemetry, Responsible AI frameworks, LLM integrations, Microservices Architecture, CI CD pipelines, AI governance principles, Event-driven architectures, AI orchestration