TMS

• Document the existing Qlik environment including current architecture, bottlenecks, and support requirements • Take on the design, development, performance optimization, and troubleshooting of Qlik Sense applications • Engage directly with business stakeholders to understand their needs and drive continuous improvement

• Document the existing Qlik environment • Design, develop, and optimize Qlik Sense applications • Troubleshoot issues and engage with stakeholders • Translate business needs into actionable solutions • Drive continuous improvement across analytics capabilities

• Manage end-to-end recruitment for IT positions supporting US State Government clients • Work closely with account managers and delivery teams to understand role requirements and timelines • Source, screen, and submit candidates across multiple IT skill sets under tight SLAs • Handle high-volume requisitions while maintaining quality and compliance standards • Coordinate interviews, follow up with candidates, and manage offer processes • Ensure adherence to state-specific hiring guidelines, documentation, and compliance requirements • Maintain accurate records in ATS and provide regular status reports to stakeholders

• Be the one building AI-powered experiences where they matter most. • The Principal Architect and AI Engineer – Agentic & Industry Solutions is a highly technical, hands-on leader responsible for designing, building, and scaling transformative AI-powered solutions on Genesys Cloud. • Working within the Innovation Solutions organization, this role drives the development of reusable Agentic AI capabilities, industry-specific solution accelerators, and intelligent workflow automation that enable organizations to fundamentally transform customer and employee experiences. • The Principal Architect and AI Engineer provides technical leadership and expertise across architecture, development, and solution delivery, collaborating with Product, Engineering, Strategic Customers, Industry SMEs, and Technology Partners to convert emerging AI technologies into scalable, market-leading solutions.

• Collaborate with stakeholders to gather and define product requirements • Manage the product backlog and prioritize features • Work closely with development teams to ensure timely delivery of product increments • Participate in Agile ceremonies and provide clear product vision

• Lead and manage large-scale data and AI programs from initiation to delivery. • Act as a bridge between business stakeholders and technical teams, ensuring clear communication and alignment. • Drive onsite-offshore coordination, ensuring seamless collaboration across geographically distributed teams. • Oversee program planning, execution, risk management, and delivery timelines. • Manage Databricks-based data platforms and solutions, ensuring scalability and performance. • Define program governance structures, KPIs, and reporting mechanisms. • Work closely with architects and engineering teams to guide data, analytics, and AI solution design. • Ensure adherence to quality, compliance, and security standards. • Identify and mitigate risks, dependencies, and bottlenecks proactively. • Provide regular updates to leadership and stakeholders on program status, risks, and outcomes. • Drive continuous improvement in delivery processes and best practices.

• Design, implement, and manage enterprise data management solutions using Informatica Intelligent Data Management Cloud (IDMC). • Leverage Informatica CLAIRE AI capabilities for intelligent data discovery, metadata management, and automated data governance. • Lead the implementation of enterprise data governance frameworks, policies, and standards. • Implement and manage Data Catalog, Data Quality, Data Integration, and Master Data Management (MDM) solutions within IDMC. • Collaborate with data architects, business stakeholders, and analytics teams to enable trusted data for reporting and AI/ML initiatives. • Define and enforce data standards, data stewardship processes, and data lifecycle management. • Configure and manage data lineage, metadata management, and data classification using Informatica tools. • Support regulatory and compliance initiatives (GDPR, CCPA, etc.) through robust governance implementations. • Provide architectural guidance and best practices for cloud data platforms and enterprise data ecosystems. • Mentor junior team members and provide technical leadership in Informatica implementations.

• Define and execute the product roadmap for the maintenance platform, including work order management, inspections, preventive maintenance, and resident communication • Partner with Operations, Engineering, and external vendors to translate business needs into scalable product solutions • Own end-to-end delivery—from requirements and prioritization through launch and iteration • Optimize workflows across key areas such as scheduling, technician productivity, and automated resident engagement • Drive integration strategy (e.g., PMS, CRM, middleware) to ensure seamless data flow and system interoperability • Leverage data and user feedback to continuously improve product performance and adoption • Support pilot programs and scale successful solutions across the portfolio • Identify opportunities to leverage AI to automate workflows (e.g., work order intake, routing, communication) • Partner with engineering on AI-enabled features such as recommendation engines, automation, and workflow optimization • Define success metrics and evaluate AI performance (accuracy, efficiency, user adoption) • Ensure responsible AI usage, including data quality, transparency, and operational reliability.

• Design, develop, and deploy AI-powered applications using LLMs such as Claude, GPT, and other foundation models. • Utilize GitHub Copilot / Claude Code to accelerate software development, testing, debugging, and documentation. • Build AI agents, copilots, and workflow automation solutions. • Design and develop AI/ML-based solutions using modern frameworks and tools • Build and maintain backend services using .NET (C#, ASP.NET Core) • Deploy, manage, and optimize applications on Microsoft Azure • Integrate AI models into production systems and APIs • Work with structured data stored in Oracle DB, including performance tuning and query optimization • Collaborate with data scientists, product managers, and cross-functional teams • Implement data pipelines and workflows for AI model training and inference • Ensure scalability, reliability, and security of AI applications • Monitor model performance and continuously improve solutions

• Design, develop, and maintain the Transactional Billing Automation platform, including tracking contract information, prepaid usage blocks, rollovers, and calculating projected usage and balances. • Build and support responsive web application and RESTful APIs to automate transactional billing operations and reduce manual processing. • Develop dynamic UI components for managing customer contracts, multi-product selections, invoice details, and billing summaries. • Implement business logic for prepaid balances, rollover amounts, block total calculations, invoice validations, and contract lifecycle management. • Collaborate with product owners, software engineers, and QA engineers to gather billing requirements and deliver scalable automation solutions. • Create reusable components, clean architecture patterns, and well-documented APIs to improve maintainability and long-term scalability. • Develop unit tests, integration tests, and automated validation processes to ensure billing accuracy and support safe application enhancements. • Participate in code reviews and enforced coding standards, security best practices, and performance optimization techniques. • Develop operational dashboards and billing reports to provide visibility into contracts, prepaid usage, rollover balances, projected customer usage, and actual consumption trends. • Follow development standards, branching strategies, and pull request workflows to deliver clean, secure, and maintainable code through reviews and testing. • Support Agile development processes, including sprint planning, backlog refinement, stand-ups, demos, and retrospectives.