AI Engineering Analyst

Job summary

Work with property, asset management, finance, and executive teams to identify operational bottlenecks, quantify their business impact, and build and deploy AI-enabled software solutions. Run structured pilots, measure adoption and outcomes, and recommend whether solutions should be scaled or discontinued.

Job details

AI Engineering Analyst We are looking for an ambitious, execution-oriented recent graduate to join our team at Pacific Reach. This role sits at the intersection of AI, technology, capital markets, and real estate operations. We do not operate with a traditional IT ticket queue or rigid corporate hierarchies. Instead, you will work directly with our asset management, property operations, capital markets and executive teams to identify operational friction points across our real estate and hospitality portfolios and build the solutions required to fix them. Because our platform spans asset-heavy investments, property management, and hospitality, the feedback loop is immediate. When you build a tool, you can deploy it directly into an active environment, watch our operators use it, and iterate in real time. Success in this role means translating messy operational workflows into clean, functional solutions that drive efficiency, optimize overhead investment, or improve data accuracy and timeliness for decision making. If a project delivers clear commercial value, we scale it; if the evidence doesn't support it, we move on quickly. Core Responsibilities Operational Discovery: Embed with our property managers, asset leads, and finance teams to map manual workflows, identify bottlenecks, and size the economic opportunity in hard numbers (operating margin, cycle time, or labor hours saved). Rapid Prototyping & AI Engineering: Build and ship functional software leveraging modern AI developer tooling (specifically Claude Code). Take hypotheses from a blank canvas to a testable version rapidly, integrating with existing systems and third-party APIs where necessary. Structured Pilot Execution: Run time-boxed pilots with named users, defined success metrics, and clear criteria for success. Track adoption telemetry and manage early deployment. Commercial & Capital Judgment: Evaluate whether a tool deserves broader operational rollout or if it should be shelved. Present findings, metrics, and recommendations directly to leadership. What You Bring Academic & Analytical Foundation: A degree in computer science, engineering, business, economics, or a related quantitative field. Strong new graduates with high raw capability and intellectual curiosity will be actively considered. Demonstrated Execution: Tangible proof you have built and shipped real things—whether that's an automated internal tool, a commercial prototype, a technical side project, or a venture you bootstrapped. What you've actually built matters more than pedigree. Modern AI Fluency: Daily, fluent use of modern AI-assisted development environments (specifically Claude Code), backed by the critical judgment to verify outputs rather than blindly trusting them. Technical Literacy: Proficiency in Python is required. You should also have working comfort with APIs, data structures, SQL, and automation tools, or a proven track record of picking up technical systems rapidly. Commercial Acumen & Empathy: The ability to sit down with a busy operator, understand where their workflow is breaking down, connect that pain point to a business case, and explain why a solution is worth building. Communication: Clear writing and verbal communication skills, with the ability to explain technical concepts to executive leadership without relying on jargon. Nice to Have Prior founder, side project, or startup experience. Familiarity with modern development ecosystems (such as TypeScript or React) and tools like Claude, Cursor, Linear, Supabase, or Slack. Exposure to real estate, property management, hospitality, financial services, or other asset-heavy industries. Experience with product methodologies, including user discovery, user stories, and structured pilot design. Experience integrating LLMs into applications, covering prompt engineering and output evaluation.

What you’ll do

Work with property, asset management, finance, and executive teams to identify operational bottlenecks, quantify their business impact, and build and deploy AI-enabled software solutions. Run structured pilots, measure adoption and outcomes, and recommend whether solutions should be scaled or discontinued.

Requirements

A degree in computer science, engineering, business, economics, or a related quantitative field is sought, with strong recent graduates considered; candidates must demonstrate that they have built and shipped real projects. Requirements include Python proficiency, fluent use of AI-assisted development tools such as Claude Code, technical comfort with APIs, data structures, SQL, and automation, plus commercial judgment and clear communication.

Listed skills

• SQL · Preferred
• AI-assisted development · Preferred
• Communication · Preferred
• prompt engineering · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• Claude Code
• AI-Assisted Development
• API Integration
• SQL
• Data Structures
• Automation
• Rapid Prototyping
• Workflow Analysis
• Pilot Design
• Commercial Analysis
• Communication
• LLM Integration
• Prompt Engineering
• Output Evaluation

Job areas

• Technology
• Software
• Data & Analytics
• Sales
• Finance & Accounting