Havenpark Communities

Solutions Engineer

• Assess how work is performed and prioritize AI opportunities based on hours returned, error reduction, and reach
• Design, build, and ship AI companions, agents, and workflow automations from prototype through production
• Integrate with HubSpot, Microsoft 365, Snowflake, property management and finance platforms, and vendor APIs
• Build on governed data models and the analytics semantic layer
• Maintain reusable patterns, prompts, tools, and evaluation sets
• Own evaluation, monitoring, exception handling, and escalation for production workflows
• Enforce human review for consequential actions involving customers, residents, money, or records of record
• Manage model usage and cost; use source control and pull requests; document solutions
• Maintain an inventory of agents, prompts, and integrations, including ownership and access
• Partner with function leaders to select problems, define success, and verify realized value
• Embed with users, observe adoption and failures, and iterate
• Train users and managers on capabilities, limitations, and escalation
• Follow AI usage policy and intake processes, involving Legal and HR when appropriate
• Implement least-privilege identities and traceable logging for agents and integrations

AI Solutions Engineer

Analytics Engineer

• Design and implement facts and dimensions in dbt using staging, intermediate, core, and mart layers
• Model slowly changing dimensions and mixed-grain snapshot sources
• Make defensible grain and materialization decisions
• Migrate legacy reports and business-critical views onto the new Core model
• Reconcile report outputs line-for-line for trusted cutovers
• Use AI coding tools for model development, test writing, and dbt/GitHub workflows
• Review, correct, and own the correctness, performance, and style of AI-assisted work
• Write dbt generic, singular, and unit tests
• Establish contracts on data-out models and treat failing CI checks as release blockers
• Integrate and document diverse source systems and their data-quality quirks
• Curate mart models and metric definitions for governed self-service and agentic AI
• Add metadata such as certification, PII level, and known issues
• Follow small-PR, shared-style-guide, version-control, and documentation practices