Python, Prompt engineering evaluation, RAG at scale, LLM system design, Cloud-native design, GenAI systems

containerization , production deployment , Agile Scrum, Azure cloud services, Microservices, Python Programming, MLops, transformer-based models, event-driven architectures, model deployment, experiment tracking, Monitoring, prompt engineering

Tensorflow, Pytorch, LangChain, embeddings, Advanced Python skills, Hugging Face, OpenAI, autonomous AI agents, prompt engineering

Deep Learning, Nlp, Gcp, Pytorch, Python Programming, Azure, Computer Vision, AWS, observability monitoring, LLMs, Hugging Face, Agentic AI solutions, vector hybrid search, LLM fine-tuning, advanced prompt engineering techniques, Vertex AI, RAG, guardrails, Document Processing, AI ML systems

Python, Tensorflow, Pytorch, Azure Cloud, MLOps tools, CI/CD

Sql, Keras, FastAPI, Amazon Web Services, Python, Docker, XGBoost, LangChain, scikit-learn, Natural Language Toolkit NLTK, Boto3, LangGraph

Java, Prometheus, Grafana, Elk Stack, Pulumi, Datadog, Jenkins, Docker, Terraform, Ansible, Azure, Kubernetes, Python, Azure DevOps, AWS, Shell Scripting Bash, Infrastructure as Code, GitOps, CI CD, GitHub Actions, Go Golang, OpenTelemetry, GitLab CI CD

API development and integration, Python, Monitoring observability or MLOps concepts, Agentic frameworks or orchestration patterns, Generative AI and LLMs, Tool calling and action execution, CI CD and modern DevOps practices

AI Integration Tools - LangChain LlamaIndex, Tensorflow, Pytorch, Machine Learning Frameworks, AI model fine-tuning techniques, Prompt engineering, AWS Bedrock, Vector Database architectures, Advanced Python programming for AI ML applications, Retrieval Augmented Generation RAG, Hugging Face, LoRA Low-Rank Adaptation techniques, Amazon SageMaker, Machine Learning architectures, Generative AI Technologies, AI system design and integration, GraphRAG methodologies, Cloud-native AI solution design, Large Language Models LLMs, AWS AI services, Agentic AI design principles