AI Agents Workflow Integration, version control systems such as Git, Python Programming Language, modern frameworks and libraries relevant to Python development, software development methodologies and best practices

Design Patterns, machine learning model architecture, reliability and scaling, inference, Software Programming

protocol buffers , API design, Distributed Systems, Python, Linux systems programming, software development and debugging tools, IOCTL interfaces, source code management, GRPC, PCIe endpoint devices, multi-threaded programming, configuration management tools, unit testing frameworks, performance optimization, host-device interactions, device memory architecture, inter-process communication technologies, GoogleTest

S3, Apis, Lambda, orchestration frameworks, inference orchestration, on-call runbooks, Monitoring, ML models, alerting, SageMaker, automated ML pipelines, SLA adherence, Glue, data ingestion, HOTW compliance, model retraining, IMR optimization, feature engineering

Testing, Coding, Software Development Lifecycle, Design Patterns, Code Review, Architecture Design, machine learning model architecture, data pipelines, software programming language, operations, model integrations, AI-native software development, Deployment

Linux, Terraform, Python, model prompt deployment, CrewAI, API services, CI/CD management, MLOps pipelines, LangGraph, AutoGen, Infrastructure Deployment, agentic workflows, system observability, real-time inference, reliability for AI services

Java, Apis, Schema Design, Spring Boot, Node.js, Spring, Typescript, Javascript, Distributed Systems, Query Optimization, Data Modelling, Consistency, Access patterns, Production-grade system design, NoSQL concepts, Partitioning, SQL databases, Indexing

Distributed Computing, Software Development, Natural Language Processing, Information Retrieval, Software Design, Networking, Programming Languages, Artificial Intelligence, Ui Design, Data Storage, accessible technologies, Security, large-scale system design