Software Engineer Principal

About The Role

As a CBRE Software Engineer Principal, you will own and lead the Forward Deployed Engineering (FDE) pod operating under a metered-funding incubation model. This is a builder-first, hands-on leadership role (40% time spent directly architecting and coding) for someone who thrives in ambiguity, has a strong bias for action, and combines deep full-stack and enterprise AI engineering expertise with business and product sense. The ideal candidate will manage and grow the attached FDE pod, work directly with business stakeholders to scope and build solutions, and drive rapid prototype-to-demo cycles that unlock new enterprise value.

What You'll Do

• Lead and manage the Forward Deployed Engineering (FDE) pod operating under a metered-funding incubation model, owning delivery outcomes and team performance.
• Operate as a hands-on architect (40% of time) — personally designing, building, and shipping enterprise-grade, full-stack AI solutions alongside the team.
• Partner directly with business and product stakeholders to translate ambiguous, open-ended problems into scoped, fundable incubation initiatives.
• Drive a rapid build-demo-iterate cadence — whiteboard concepts, build working prototypes, and demo to clients/stakeholders on tight cycles.
• Architect and implement enterprise-grade AI systems, including multi-agent workflows, RAG pipelines, and LLM-based solutions integrated into real client environments.
• Build connectors and secure data pipelines between client/business systems and AI platforms, ensuring scalability and reliability in production.
• Recruit, mentor, and grow a high-performing engineering team, instilling a builder-first culture and strong technical bar.
• Act as the critical link between field/incubation learnings and the broader product and engineering roadmap, surfacing insights that shape strategic direction.
• Manage incubation funding and resourcing decisions in a metered-funding model — balancing speed of delivery against business case justification.
• Lead executive-level demos and readouts, articulating technical solutions and business value clearly to both technical and non-technical audiences.
  
  

What You'll Need

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 8+ years of progressive experience in software engineering, applied AI/ML, or full-stack architecture, including direct people-management or pod-leadership experience.
• Prior experience in a customer-facing, forward-deployed, or consulting/implementation capacity is strongly preferred.
• Background from a top-tier technology company (FAANG/equivalent), high-growth product organization, or premier consulting firm is strongly preferred.
  
  

Technical Skills

• Full-Stack Engineering: Expert-level proficiency across the stack — backend, frontend, APIs, and data pipelines — with hands-on coding ability (Python, TypeScript/Node.js, Java, or equivalent).
• Enterprise-Grade AI: Demonstrable depth in LLMs, multi-agent systems, RAG, embeddings, vector databases, and prompt engineering, with experience deploying these in production enterprise environments.
• Cloud & MLOps: Hands-on experience with AWS/GCP/Azure and MLOps tooling for deploying and scaling AI systems.
• API & Systems Integration: Experience designing and integrating APIs and connectors with enterprise systems (e.g., Salesforce, ServiceNow, Palantir).
• Architecture & Delivery: Strong grasp of SDLC, agile methodologies, and pragmatic architecture decision-making in fast-moving, ambiguous environments.
  
  

Leadership and Business Acumen

• Proven builder mindset — prefers shipping working solutions over lengthy planning cycles; strong bias for action.
• Demonstrated ability to build, mentor, and scale high-performing engineering teams from the ground up.
• Strong product and business sense — able to evaluate technical decisions through the lens of business value and ROI.
• Comfortable operating with significant ambiguity, incomplete requirements, and evolving scope.
• Experience operating in or managing metered-funding, incubation, or innovation-lab style engagement models is a strong plus.
  
  

Good To Have

• Agentic AI hands-on experience — designing and deploying autonomous, proactive multi-agent systems in production.
• Familiarity with containerization technologies (Docker, Kubernetes).
• Prior experience in commercial real estate or adjacent industries.
• Experience presenting to and influencing C-suite or senior executive stakeholders.