What are the responsibilities and job description for the AI architect position at Infinite Computer Solutions?
AI architect JD
Looking for a Customer Facing Technical Architect - AI and GenAI Platforms. We are working to leverage generative AI technologies to streamline, enhance, and automate the complete phase of the software development lifecycle (SDLC) such as
Automated Documentation
AI-Assisted Design Tools
Prototyping
Code Generation
Code Completion and Suggestions
Automated Test Case Generation
AI-Driven Testing Tools
CI/CD Automation
Infrastructure as Code (IaC)
Predictive Maintenance
Automated Monitoring
Automated Documentation Generation
Chatbots and Virtual Assistants
Design AI Solutions
Architect and design scalable, reliable, and high-performance AI solutions leveraging the capabilities of Multi-Cloud Platforms (GCP, Azure, AWS). Design, develop, and implement Generative AI models and algorithms LLM models (Falcon, Llama2), Google (PaLM, Gemini), Open AI
LLM Ops
Productionize models model training, model deployment, model serving, and model monitoring. Optimize Generative AI models for improved performance, scalability, and efficiency.
Client Consultation
Conduct thorough consultations with clients to comprehend their business goals, challenges, and requirements.
Act as a trusted advisor, providing insights into how Gen AI solutions can drive value and enhance business processes.
Prototyping and Proof of Concept
Develop prototypes and proof of concept demonstrations to showcase the feasibility and potential impact of proposed Gen AI solutions.
Iterate on prototypes based on client feedback and technical feasibility.
> Proficiency in the following languages, frameworks, and tools is preferred:
> Programming and scripting languages: Python, C/C , Make, Java, JSP, Perl, Shell, JavaScript, TypeScript
> Structured and NoSQL databases: Informix, Oracle, PostgreSQL, MongoDB, Cassandra
> Modernization of monolithic applications and legacy app migrations to microservices architecture
> Database and dataset migrations, SQL conversion scripting
Virtualization tools: VMware, Vagrant, Docker, Podman
Containerization tools: Kubernetes (K8s), OpenShift, Amazon EKS, Helm
> Cloud platforms: AWS, Google Cloud Platform (GCP), Microsoft Azure
> CI/CD tools: Jenkins, GitCI, Argo
Looking for a Customer Facing Technical Architect - AI and GenAI Platforms. We are working to leverage generative AI technologies to streamline, enhance, and automate the complete phase of the software development lifecycle (SDLC) such as
Automated Documentation
AI-Assisted Design Tools
Prototyping
Code Generation
Code Completion and Suggestions
Automated Test Case Generation
AI-Driven Testing Tools
CI/CD Automation
Infrastructure as Code (IaC)
Predictive Maintenance
Automated Monitoring
Automated Documentation Generation
Chatbots and Virtual Assistants
Design AI Solutions
Architect and design scalable, reliable, and high-performance AI solutions leveraging the capabilities of Multi-Cloud Platforms (GCP, Azure, AWS). Design, develop, and implement Generative AI models and algorithms LLM models (Falcon, Llama2), Google (PaLM, Gemini), Open AI
LLM Ops
Productionize models model training, model deployment, model serving, and model monitoring. Optimize Generative AI models for improved performance, scalability, and efficiency.
Client Consultation
Conduct thorough consultations with clients to comprehend their business goals, challenges, and requirements.
Act as a trusted advisor, providing insights into how Gen AI solutions can drive value and enhance business processes.
Prototyping and Proof of Concept
Develop prototypes and proof of concept demonstrations to showcase the feasibility and potential impact of proposed Gen AI solutions.
Iterate on prototypes based on client feedback and technical feasibility.
> Proficiency in the following languages, frameworks, and tools is preferred:
> Programming and scripting languages: Python, C/C , Make, Java, JSP, Perl, Shell, JavaScript, TypeScript
> Structured and NoSQL databases: Informix, Oracle, PostgreSQL, MongoDB, Cassandra
> Modernization of monolithic applications and legacy app migrations to microservices architecture
> Database and dataset migrations, SQL conversion scripting
Virtualization tools: VMware, Vagrant, Docker, Podman
Containerization tools: Kubernetes (K8s), OpenShift, Amazon EKS, Helm
> Cloud platforms: AWS, Google Cloud Platform (GCP), Microsoft Azure
> CI/CD tools: Jenkins, GitCI, Argo
