What are the responsibilities and job description for the Yardi Administrator position at Vichara?
Key Responsibilities
System Administration & Configuration
- Manage, configure, and maintain Yardi modules (Voyager, RENTCafé, Budgeting & Forecasting, CRM, Account Trees, etc.).
- Perform system upgrades, patch installations, and release testing.
- Configure workflows, security roles, permissions, user accounts, and property setups.
- Customize dashboards, reports, menus, and data interfaces based on business needs.
Data Management & Reporting
- Oversee data integrity, troubleshoot discrepancies, and conduct data audits.
- Create and maintain custom reports using Yardi Report Scheduler or SQL-based reporting tools. Support financial reporting, budgeting, and property financial processes.
- Manage imports/exports, bulk data operations, and integration with third-party systems.
Technical Support & Troubleshooting
- Act as the primary point of contact for Yardi system issues and user support.
- Resolve application errors, functional issues, and system performance challenges.
- Work closely with internal IT teams and Yardi support to diagnose and fix complex problems.
- Provide training and documentation for end-users.
Process Optimization
- Analyze existing workflows and recommend improvements for efficiency and accuracy.
- Support new property onboarding, acquisition setups, and portfolio expansions.
- Implement automation, process enhancements, and system best practices.
Required Qualifications
- Bachelor’s degree in Information Technology, Computer Science, Finance, or related field (preferred). Minimum 5 years of hands-on experience with Yardi Voyager administration or related Yardi platforms. Strong understanding of property management, accounting workflows, and real estate operations.
- Proficiency with SQL queries, data validation, and reporting tools.
- Experience with system integrations, APIs, and data migration processes.
- Familiarity with modules like PAYScan, Job Cost, Affordable Housing, Commercial, and Residential (as applicable).
Key Skills & Competencies
- Strong analytical and problem-solving skills.
- Excellent communication and cross-functional collaboration abilities.
- Ability to manage multiple priorities and meet deadlines.
- High attention to detail and commitment to data accuracy.
- Ability to work independently as well as part of a team.
Preferred Skills (Nice to Have)
- Experience with MRI, RealPage, or other property management systems.
- Basic scripting or automation experience (PowerShell, Python, etc.).
- Prior involvement in system implementations or major upgrades.
Responsibilities
GenAI Framework Development – Develop custom frameworks using GPT APIs or LLaMA for alternate data analysis and insights generation. Optimize LLM usage for investment-specific workflows, including data enrichment, summarization, and predictive analysis.
Automation & Orchestration – Design and implement document ingestion workflows using tools such as n8n (or similar orchestration frameworks). Build modular pipelines for structured and unstructured data.
Infrastructure & Deployment – Architect deployment strategies on cloud (AWS, GCP, Azure) or private compute environments (CoreWeave, on-premises GPU clusters). Ensure high availability, scalability, and security in deployed AI systems.
Required Candidate Profile
Strong proficiency in Python with experience in frameworks such as TensorFlow or PyTorch.
2 years of experience in Generative AI and Large Language Models (LLMs).
Experience with VectorDBs (e.g., Pinecone, Weaviate, Milvus, FAISS) and document ingestion pipelines.
Familiarity with data orchestration tools (e.g., n8n, Airflow, LangChain Agents).
Understanding of cloud deployments and GPU infrastructure (CoreWeave or equivalent).
Proven leadership skills with experience managing cross-functional engineering teams.
Strong problem-solving skills and ability to work in fast-paced, data-driven environments.
Experience with financial or investment data platforms.
Knowledge of RAG (Retrieval-Augmented Generation) systems.
Familiarity with frontend integration for AI-powered applications.
Exposure to MLOps practices for continuous training and deployment.