RQ- Applications Architect - Senior

Deliverables:

• Leadership experience in the development and implementation of application architectures at the specified experience level.
• Facilitation skills to engage multiple stakeholders involving I&IT solutions, security, privacy, and accessibility considerations.
• Solid experience and knowledge of Information Architecture, Data Modelling, BI Analytics.
• Experience in the use of Computer Aided Software Engineering (Case) tools (i.e. Power Designer, Visio) and other software tools.
• Experience in using AI for data analysis which blends traditional strengths with new AI-centric abilities:
  • Prompt Engineering:
    Communicating effectively with AI tools to get desired analysis and insights.
  • Machine Learning Literacy:
    Understanding how ML models work (prediction, pattern recognition) and when to apply them.
  • Automation Mastery:
    Using AI to automate data collection, cleaning (ETL), and workflow building.
  • Generative AI for Analytics:
    Using AI to speed up tasks like summarization or initial data exploration.
• Solid experience and knowledge of cloud native technology and architecture to support applications with high sensitive data such as Azure App Services and RESTful API.
• Extensive experience with microservice architecture using containers – specifically with Tanzu (formerly Pivotal Cloud Foundry).
• Extensive experience with at least three different platforms (e.g. Midtier, Mobile), operating systems (e.g. Solaris, Windows), environments, database technologies (e.g. MS SQL), programming languages (e.g. Java, C#, JavaScript), and communications protocols (ftp, http, smtp, ntp, tcp/ip, udp, icmp).
• Knowledge of and experience with MLITSD application patterns and infrastructure.
• Experience in structured methodologies for the design, development and implementation of applications.
• Extensive experience in systems analysis and design in large systems environments.
• Awareness of emerging technologies, trends and direction.
• Excellent analytical, problem-solving and decision‑making skills; verbal and written communication skills; interpersonal and negotiation skill.
• Experience in OPS Governance processes, Target State Architecture (TSA) and different architecture domains deliverables.

Experience and Skill Set Requirements:

Must Haves:

• 3+ years of experience in the development and implementation of applications and databases.
• Demonstrated experience in providing information architecture interpretation advice and expertise to other project and/or enterprise level I&IT project teams.
• Demonstrated experience in delivering architectural artefacts as required by the project to successfully pass through the project review governance points.
• Experience in the use of Computer Aided Software Engineering (Case) tools (i.e. Power Designer, Visio) and other software tools.

Nice to have:

• Experience in using AI for data analysis which blends traditional strengths with new AI-centric.

• 3+ years of experience in the development and implementation of applications and databases.
• Demonstrated experience in providing information architecture interpretation advice and expertise to other project and/or enterprise level I&IT project teams.
• Demonstrated experience in delivering architectural artefacts as required by the project to successfully pass through the project review governance points.
• Demonstrates previous leadership in complex application architecture reviews and assessments, development and/or support projects for enterprise initiatives.
• Experience in the use of Computer Aided Software Engineering (Case) tools (i.e. Power Designer, Visio) and other software tools.
• Experience in using AI for data analysis which blends traditional strengths with new AI-centric abilities:
  • Prompt Engineering:
    Communicating effectively with AI tools to get desired analysis and insights.
  • Machine Learning Literacy:
    Understanding how ML models work (prediction, pattern recognition) and when to apply them.
  • Automation Mastery:
    Using AI to automate data collection, cleaning (ETL), and workflow building.
  • Generative AI for Analytics:
    Using AI to speed up tasks like summarization or initial data exploration.

• Experience…