Checking job availability...
Original
Simplified
- Design and architect AI components and services within a Service-Oriented Architecture (SOA) framework.
- Define system components, interfaces, and APIs to enable seamless AI integration into scalable software platforms.
- Ensure modularity, reusability, and maintainability of AI services within enterprise architectures.
- Work closely with business stakeholders to understand requirements and translate them into AI-driven workflows and processes.
- Conduct feasibility analysis of AI solutions and evaluate their impact on business objectives.
- Define key performance indicators (KPIs) and success metrics for AI-driven processes.
- Architect and manage data science layers, including feature engineering, model management, and data pipelines.
- Oversee AI model lifecycle management, from development to deployment and monitoring.
- Integrate machine learning models and AI components into existing product stacks, frameworks, and applications.
- Design AI architectures that support high-performance, distributed, and real-time processing.
- Ensure efficient data flow and processing within AI-driven applications.
- Optimize computational resources and AI infrastructure to balance cost, scalability, and efficiency.
- Collaborate with software engineers, data engineers, and DevOps teams to align AI solutions with broader system architectures.
- Establish best practices for AI model deployment, CI/CD pipelines, and AI-driven application monitoring.
- Provide mentorship and technical leadership in AI architecture and solution design.
- 8+ years of experience in AI architecture, software engineering, or data science.
- Proven track record in designing and implementing AI solutions within SOA architectures.
- Hands-on experience integrating AI models into enterprise software products.
- Expertise in AI/ML frameworks such as PyTorch, Scikit-learn.
- Strong proficiency in Python and familiarity with AI model deployment frameworks.
- Deep understanding of data science layers, feature stores, model registries, and data lakes.
- Experience in designing APIs and microservices for AI-driven applications.
- Knowledge of MLOps, model versioning, and monitoring best practices.
- Strong understanding of data pipelines, streaming architectures (Kafka, Flink), and real-time AI processing.
- Ability to bridge the gap between business objectives and AI capabilities.
- Experience in conducting AI feasibility studies and risk assessments.
- Strong problem-solving skills with a business-driven mindset.
- Certifications in AI, Data Science, ML, or DL
- Design and architect AI components and services within a Service-Oriented Architecture (SOA) framework.
- Define system components, interfaces, and APIs to enable seamless AI integration into scalable software platforms.
- Ensure modularity, reusability, and maintainability of AI services within enterprise architectures.
- Work closely with business stakeholders to understand requirements and translate them into AI-driven workflows and processes.
- Conduct feasibility analysis of AI solutions and evaluate their impact on business objectives.
- Define key performance indicators (KPIs) and success metrics for AI-driven processes.
- Architect and manage data science layers, including feature engineering, model management, and data pipelines.
- Oversee AI model lifecycle management, from development to deployment and monitoring.
- Integrate machine learning models and AI components into existing product stacks, frameworks, and applications.
- Design AI architectures that support high-performance, distributed, and real-time processing.
- Ensure efficient data flow and processing within AI-driven applications.
- Optimize computational resources and AI infrastructure to balance cost, scalability, and efficiency.
- Collaborate with software engineers, data engineers, and DevOps teams to align AI solutions with broader system architectures.
- Establish best practices for AI model deployment, CI/CD pipelines, and AI-driven application monitoring.
- Provide mentorship and technical leadership in AI architecture and solution design.
- 8+ years of experience in AI architecture, software engineering, or data science.
- Proven track record in designing and implementing AI solutions within SOA architectures.
- Hands-on experience integrating AI models into enterprise software products.
- Expertise in AI/ML frameworks such as PyTorch, Scikit-learn.
- Strong proficiency in Python and familiarity with AI model deployment frameworks.
- Deep understanding of data science layers, feature stores, model registries, and data lakes.
- Experience in designing APIs and microservices for AI-driven applications.
- Knowledge of MLOps, model versioning, and monitoring best practices.
- Strong understanding of data pipelines, streaming architectures (Kafka, Flink), and real-time AI processing.
- Ability to bridge the gap between business objectives and AI capabilities.
- Experience in conducting AI feasibility studies and risk assessments.
- Strong problem-solving skills with a business-driven mindset.
- Certifications in AI, Data Science, ML, or DL