Product Manager - Sustainability

Since 2003, Entrata has evolved from a visionary, student-led startup into a global leader in AI-driven property management technology.

Today, we power the industry's most essential operating system, serving owners and residents worldwide through a comprehensive suite of intelligent leasing, payment, and communication tools powered by cutting-edge AI.

With a proven track record of sustained growth and a global team of more than 2,200 employees, we offer the rare combination of established stability and high-velocity innovation. Recognized by the Silicon Slopes Hall of Fame and the Utah Business Fast 50, Entrata fosters a culture of radical transparency and entrepreneurial energy.

At Entrata, we create an environment where different perspectives are valued and respected. Those perspectives challenge assumptions, strengthen our decisions, and raise the bar as we reshape the global living experience through AI-powered solutions.

Responsibilities

Supports the development of long-term product strategy and vision by providing analysis, research, and input based on customer feedback, market trends, and internal priorities.

Contributes to the creation of product value statements, product performance metrics, and feedback loops to monitor customer satisfaction.

Participates in executing market validation activities for released epics, including customer conversations, interviews, and research.

Assists in defining and prioritizing the product backlog, ensuring alignment with broader product strategy and guiding documents.

Drafts and contributes to epics, user stories, and detailed requirements for product updates and projects.

Supports product strategy and roadmap discussions by preparing materials, articulating key findings, and offering recommendations.

Collaborates with cross-functional partners across Product, Engineering, Marketing, Sales, and Services to support the delivery of product updates and go-to-market activities.

Provides product information and training support to Sales and Services teams as needed.

Assists in reviewing feature requests and evaluating viability, scope, and alignment with product goals.

Contributes to implementation process improvements in coordination with Services.

Leverages AI-augmented capabilities to enhance research, drafting, analysis, and workflow efficiency across product processes.

Designs and applies structured, multi-step prompting to support product research, requirement generation, competitive analysis, and cross-functional communication.

Supports the integration of AI tooling, workflow automation, and agent-based systems to improve product delivery, reduce manual effort, and enhance team throughput.

Participates in evaluating the performance of AI-driven processes or outputs by identifying drift, hallucinations, inefficiencies, or bias and recommending prompt or workflow adjustments.

Essential Functions

2+ years of experience in product management or related roles within the software industry.

Conducts research, analysis, and customer validation activities to inform product decisions.

Develops and maintains product documentation, including epics, user stories, and requirements.

Collaborates with cross-functional stakeholders to ensure alignment on product priorities and delivery.

Contributes to product backlog refinement and prioritization activities.

Applies AI-driven data analysis techniques to help identify patterns, trends, and opportunities in customer feedback, market research, or product performance data.

Uses AI tools to accelerate productivity in ideation, analysis, and delivery workflows.

Travels domestically for client meetings, industry events, and company gatherings as required to maintain business relationships and achieve objectives.

Ability to prioritize tasks effectively by meeting deadlines and managing workload efficiently.

Maintain professional interaction with internal and external stakeholders

Ability to work in a fast-paced and high-stress environment

Minimum Qualifications

Intermediate understanding of product management principles, customer needs, and company processes.

Ability to apply guidelines, best practices, and analysis to moderately complex product tasks.

Strong written and verbal communication skills for conveying product requirements and findings to varied audiences.

Ability to adapt communication style to stakeholders and contribute to collaborative problem-solving.

Demonstrated ability to organize work, follow established procedures, and exercise discretion in resolving non-standard issues.

Advanced prompting expertise, including the ability to design multi-step prompts with embedded logic, recursion, and context chaining to produce highly reliable outputs.

Context engineering proficiency for managing structured and unstructured inputs to optimize LLM reasoning and relevance.

Working knowledge of transformer-based LLM architectures, attention mechanisms, tokenization, context windows, RAG approaches, and common model failure modes.

Proficiency in workflow automation using AI tools, LLMs, or agentic systems to orchestrate complex, multi-step processes with human-in-the-loop controls where appropriate.

Familiarity with tool integration and agentic reasoning, including the ability to chain LLMs with APIs, vector databases, or code execution environments.

Ability to critically evaluate AI outputs for drift, hallucination, bias, or inefficiencies and refine prompts or processes accordingly.

Experience leveraging AI tooling for analytics, pattern detection, and predictive modeling to support product decisions.

Demonstrated track record of using AI to significantly improve efficiency, throughput, or quality across business or technical workflows.

Education and Experience Requirements

Bachelor’s degree and a minimum of 2 years of related experience; or a relevant advanced degree without experience; or equivalent work experience.

Experience contributing to product teams or supporting product development activities.

AI Proficiency Requirements For All Product Roles

Advanced prompting expertise: Capable of designing sophisticated, multi-step prompts with embedded logic, recursion, and context chaining to produce highly specific and reliable outputs across diverse domains.

Context engineering mastery: Skilled in managing structured and unstructured inputs across system and user prompts to optimize LLM reasoning, retention, and relevance.

Working knowledge of LLM architectures: Understanding of transformer-based architectures, including attention mechanisms, tokenization and context window limitations, fine-tuning strategies, retrieval-augmented generation (RAG), and the typical failure modes of frontier models.

Workflow Automation proficiency: Proven experience designing and implementing AI-augmented workflows that reduce manual effort and enhance throughput and precision, especially using LLMs and AI agents in the orchestration of complex, multistep processes, including human-in-the-loop safeguards where appropriate

Tool integration & agentic reasoning: Familiarity with chaining LLMs with tools, APIs, vector databases, or code execution environments to complete dynamic, multi-context tasks.

Critical evaluation of AI performance: Ability to detect model drift, hallucinations, bias, or inefficiencies—and to refine prompt or architecture design accordingly.