Applied AI Engineer

About the Team & This Opportunity

The Data & Analytics team is the engine behind WS Development's digital transformation. We're building the data foundation and AI capabilities that power decision-making, automation, and competitive advantage across the organization and we're doing it from the ground up, which means every technical and architectural decision we make today shapes how WS uses data for years to come.

This is a team that moves fast, thinks big, and ships real work. We sit close to senior leadership and partner directly with business teams across leasing, finance, development, legal, and operations. You'll see the full picture of how a complex, multi-dimensional real estate company operates and you'll be building the AI systems that make it run better.

We're looking for an Applied AI Engineer who wants to be a core part of this story: someone who combines genuine technical depth with the instincts of a builder, who's energized by hard problems in a fast-moving field, and who thrives in an environment where the work is ambiguous, the stakes are real, and the impact is visible. This is a hands-on role with real autonomy. You'll take ideas from concept to production, own the technical delivery, and ship work that meaningfully changes how WS operates day-to-day.

What You'll Do

• Design and build AI solutions end-to-end from discovery and scoping through production deployment and iteration with clear success metrics tied to real business outcomes.
• Partner closely with stakeholders across leasing, finance, operations, development, legal, and other departments to identify inefficiencies and translate them into concrete AI and automation use cases.
• Design and deploy agentic systems for business workflows, including orchestration logic, tool and API integrations, retrieval patterns (RAG), guardrails, and human-in-the-loop flows.
• Develop internal AI applications that put new capabilities directly in the hands of business teams tools that people actually use, and that change how they work.
• Build robust evaluation and observability into AI systems, ensuring they stay reliable and performant in production across quality, latency, and cost dimensions.
• Help WS scale AI responsibly on proprietary data by contributing to governance frameworks, guardrails, and responsible use practices.
• Create reusable patterns, templates, and shared infrastructure that enable business units to prototype safely and accelerate AI adoption company wide.

Why This Role

This isn't an AI role where you're maintaining pipelines or building proofs-of-concept that never ship. You'll be doing real applied AI work building systems that handle real data, serve real users, and solve problems that matter to a sophisticated organization. You'll have autonomy, visibility to senior leadership, and the satisfaction of seeing your work make a measurable difference.

You'll also be joining at the right moment. WS is a company with deep roots and a serious commitment to doing this right, not just fast. The Data & Analytics team is early-stage enough that your contributions will shape the culture and architecture and established enough that you'll have the resources and organizational support to actually execute. It's a rare combination.

Requirements

• Bachelor's or Master's degree in Engineering, Computer Science, Mathematics, or a related field or equivalent experience.
• 3+ years building and deploying software, data, or AI/ML solutions in production environments.
• Strong Python skills and comfort integrating APIs and external services.
• Hands-on experience using modern LLMs and AI frameworks (e.g., Anthropic, OpenAI, LangGraph, or similar) to build production applications.
• Experience implementing Retrieval-Augmented Generation (RAG) patterns.
• Experience designing and deploying agentic architectures, including multi-step workflows, tool use, and orchestration logic.
• Experience with evaluation pipelines, observability tooling, and feedback loops to measure AI system quality and performance.
• Comfort working with enterprise data realities: permissions, sensitive data, messy inputs, and governance requirements.
• Fluency with AI coding assistants (e.g., Claude Code) to accelerate development and build more effective solutions.
• A builder's mindset: you're energized by hard problems, comfortable with ambiguity, and genuinely excited about what's possible in this field.
• Excellent communication and stakeholder partnership skills — you know how to work directly with non-technical business teams, scope problems well, and deliver solutions that land.