AI Solutions Architect

Design, develop, and oversee end-to-end implementation of the new GM GenAI platform and its related business use cases.

Develop architectural approaches for AI software and hardware integration with emphasis on quality, performance, resiliency, and reusability.

Collaborate with business and IT stakeholders to understand and fulfill business needs objectives.

Lead cross-disciplinary teams to deliver technical solutions that align with business priorities and expectations.

Identify, prioritize and execute tasks in the software development life cycle.

Establish standards and lead the charge on automation for end-to-end SDLC efficiency.

Mentor team members in technical design and development best practices

Drive platform performance, scalability resiliency testing

Implement hardware upgrade software enhancement to meet global performance expectations.

Address regulatory performance driven requirements for regional/localization of infrastructure platform.

Conduct research prototyping to evaluate and identify new solutions to enhance platform and team capabilities.

Monitor AI industry trends and stay abreast of advancements in AI, machine learning, and data science to continuously innovate and improve solutions., * Design, develop, and oversee end-to-end implementation of the new GM GenAI platform and its related business use cases.

• Develop architectural approaches for AI software and hardware integration with emphasis on quality, performance, resiliency, and reusability.
• Collaborate with business and IT stakeholders to understand and fulfill business needs objectives.
• Lead cross-disciplinary teams to deliver technical solutions that align with business priorities and expectations.
• Identify, prioritize and execute tasks in the software development life cycle.
• Establish standards and lead the charge on automation for end-to-end SDLC efficiency.
• Mentor team members in technical design and development best practices
• Drive platform performance, scalability resiliency testing
• Implement hardware upgrade software enhancement to meet global performance expectations.
• Address regulatory performance driven requirements for regional/localization of infrastructure platform.
• Conduct research prototyping to evaluate and identify new solutions to enhance platform and team capabilities.
• Monitor AI industry trends and stay abreast of advancements in AI, machine learning, and data science to continuously innovate and improve solutions.

Extensive experience in designing implementing multi-tier (including microservices) application platforms.

Proven ability to plan and lead delivery by a functionally diverse and geographically dispersed team.

Possess consistent record for delivering projects on time and on budget

High coding proficiency in Python and Unix scripting

In-depth knowledge of relational databases (e.g., Oracle, MySQL) and NoSQL databases (e.g., MongoDB), and large structured unstructured dataset processing

Knowledge in full range of front-end languages, libraries frameworks (e.g., HTML/ CSS, JavaScript, XML, React, jQuery)

Strong communication skills to effectively collaborate with various stakeholders.

Critical thinking and problem-solving skills are essential.

Experience Desire

Experience implementing data analytics / AI solutions.

Knowledge of machine learning frameworks like TensorFlow or PyTorch, LLM fine-tuning, Retrieval Augmented Generation (RAG) and tools for agentic solutions.

skills:

AI,AI solutions,HTML/ CSS,data analytics,XML,Retrieval Augmented Generation (RAG),hardware integration,jQuery,JavaScript,LLM,machine learning,microservices,MongoDB,MySQL,NoSQL databases,Oracle,front-end languages,Python,PyTorch,React,relational databases,software development life cycle,SDLC,machine learning frameworks,TensorFlow,Unix scripting,Strong communication skills,Critical thinking and problem-solving,performance driven,automation,budget,business priorities,business needs,prototyping,data science,delivering projects,technical design,infrastructure,innovate,Mentor team members,application platforms,Conduct research,scalability,end-to-end implementation,testing,business use cases