embedding pipelines, vector search, observability in GenAI applications, scalable microservices, cloud-native delivery, model safety, agentic workflows, prompt optimization, LLM-integrated systems, multi-step task orchestration, context management, Cost Optimization, containerized workloads

Sql, Gcp, Neo4j, Azure, Python, AWS, LangChain, LLMs, Cypher, LangGraph, Amazon Neptune, Knowledge Graphs

lifecycle management , Devops, feedback loops, enterprise technologies, AI application engineering, retrieval-augmented generation architectures, Monitoring, build and release workflows, agentic systems, workflow automation, platform integration, CI CD pipelines, evaluation methods, cost-aware AI design, observability

Tensorflow, Ml, Java, Kotlin, Kubernetes, Sql, Python, Microservices, AWS, LLMs, Ai

Sql, Gcp, Neo4j, Azure, Python, AWS, LangChain, LLMs, Cypher, LangGraph, graph query languages, RAG agents, Amazon Neptune, Knowledge Graphs

Rtp, Microservices, Kafka, Asterisk, Node.js, Kubernetes, Python, Docker, vector DBs, LLMs, Redis Streams, message brokers, Go, ASR, CI CD, SIP, CPaaS, TTS, freeswitch, WebSockets

Python, Rabbitmq, New Relic, Django, Elk, Redis, PostgreSQL, Claude, Vector databases, Foundational LLMs, RAG, LangGraph, Fine-tuning LLMs

lifecycle management , Devops, evaluation methods, AI application engineering, enterprise AI platforms, feedback loops, Monitoring, cost-aware AI design, build and release workflows, observability, operationalizing AI-enabled systems, agentic systems, platform integration, CI CD pipelines, workflow automation