AI Solutions Architect

Randstad
New York, NY, United States
25 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Compensation
$120,182.0 - $140,982.0
Working hours
Regular working hours
Job source

Tech stack

JavaScript (Programming Language) Artificial Intelligence Unix Cascading Style Sheets (CSS) Continuous Integration Relational Databases Github Hardware Design JQuery Python (Programming Language) PostgreSQL Machine Learning
+22 more
Microsoft SQL Server MongoDB MySQL NoSQL Oracle (Applications) Systems Development Life Cycle Tensorflow Shell Script Software Engineering PL-SQL SQL Databases Extensible Markup Language (XML) Pytorch ReactJS Transfer Learning Delivery Pipeline Generative AI Data Analytics Bitbucket Jenkins Programming Languages Microservices

Job description

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.

Requirements

7 years of experience with CI/CD process similar to Horizon/Jenkins/XLR is a plus

  • Experience with RDBMS like Oracle, MS-SQL and Postgres is plus.

  • Experience with Python and Shell scripting is plus

  • Github/Bitbucket/Jenkins/XLR/CodePipeline

  • SQL/PL/SQL

skills:

AI,AI solutions,HTML/ CSS,data analytics,XML,Retrieval Augmented Generation (RAG),hardware integration,jQuery,JavaScript,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,LLM fine-tuning,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

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