Spark SQL, Tensorflow, Pytorch, Linux, Apache Kafka, Databricks, Api, Keras, Python, Gemini API, Ai, OpenAI API, Apache Parquet, AI Evaluation, low latency, Responsible AI, Claude API, Gemini, Model Quantisation, Prompt Injection

Phoenix, Datadog, Python, LLM-based systems, OpenTelemetry, Langfuse, evaluation frameworks, multi-agent environment, Arize

Celery, Neo4j, Elasticsearch, Python, FastAPI, Kubernetes, Airflow, pgvector, Argo Workflows, Qdrant, Pinecone, Prefect, OpenSearch, LangGraph, Temporal, DSPy, Microsoft AutoGen, Haystack, LangChain, CrewAI, PydanticAI, Semantic Kernel, Dagster, Milvus, Weaviate, LlamaIndex

data engineering , ML Libraries (scikit-learn), Version Control (Git), PyTorch), Containerization (Docker), Deep Learning Frameworks (TensorFlow, Data Processing (pandas, Orchestration (Kubernetes), NumPy), Java, Spring Boot, Python, Machine Learning, Distributed Systems, Artificial Intelligence, Restful Services, Agentic AI, Microservices Architecture, API Design Principles, Event-driven Architectures

Machine Learning, Distributed Systems, Saas, tool integration, retrieval-based architectures, orchestration technologies, modern LLMs, prompt optimisation, Ai, AI agents, architectural standards

Cloud Architecture, Devops, Git, Pandas, MLops, Gcp, Docker, FastAPI, Azure, Python, vector search, reranking models, unstructured data embedding, LLM applications, Langfuse, RAG, document parsing

Kafka, Spring Boot, Grafana, JIRA, Datadog, Nosql, Tensorflow, Pytorch, Docker, Swagger, Python, AWS, Java, Google Cloud, Sql, New Relic, Rabbitmq, Django, Jenkins, FastAPI, Postman, Azure, GitHub Actions, GitLab CI, RESTful API design

pruning , Machine Learning, Cpu, Gpu, Pytorch, GGML, TensorRT, llama.cpp, acceleration, NPU, ONNX Runtime, real-time systems, ML frameworks, quantization, model optimization

Python, model SDKs, AWS Strands, AWS Bedrock, GLM, Azure AI Foundry, Gen AI, LangGraph, LLMOps practices, DeepSeek, Qwen, Google Vertex AI, vector DBs