Salesforce Developer Principal AI Engineer
Role details
Job location
Tech stack
Job description
CI/CD, CrewAI LangChain Operations Leadership Consulting Management Innovation Communication Observability Mortgage Loans Responsible AI Microsoft Azure Trustworthiness Knowledge Graph Machine Learning Containerization Platform Mindset Edge Intelligence Project Management Influencing Skills Program Management Workflow Management Amazon Web Services Facility Management Resource Allocation Predictive Modeling Property Management Software Engineering Lifecycle Management Investment Management Commercial Real Estate Artificial Intelligence Real Estate Investments Concept Drift Detection Software Design Patterns Python (Programming Language) Generative Artificial Intelligence MLOps (Machine Learning Operations) Artificial Intelligence Infrastructure, As a CBRE Principal AI Engineer, you will shape enterprise intelligence by architecting, building, and scaling cutting-edge AI/ML solutions and intelligent platforms end-to-end, from inception through deployment and ongoing operations, combining deep AI engineering expertise with a product and platform mindset to deliver production-grade, enterprise-scale AI products.
This job is part of the Software Engineering job function. They are responsible for successfully executing and monitoring system improvements to increase efficiency.
What You'll Do:
- Lead the full lifecycle of AI-powered platforms - inception, architecture, development, deployment, and iteration. Apply framework thinking and architectural pattern expertise to build systems that scale, evolve, and minimize tech debt over time.
- Design and implement the full spectrum of AI/ML capabilities - predictive models, generative AI, agentic frameworks, RAG pipelines, and conversational systems - as integrated components of a coherent product architecture rather than isolated solutions.
- Operationalize LLM-powered experiences including multi-turn dialogue systems, virtual assistants, and knowledge graph-enhanced retrieval; apply enterprise fine-tuning techniques (DPO, ORPO, SPIN) to align models with domain-specific workflows and knowledge.
- Embed responsible AI principles across the development lifecycle - covering bias detection, model explainability, adversarial risk, and compliance - ensuring AI systems are trustworthy, auditable, and aligned with enterprise standards.
- Build production-grade MLOps pipelines with end-to-end model lifecycle management, monitoring, drift detection, and performance observability baked in by design.
- Translate platform architecture and AI capabilities into strategic recommendations for executive audiences; drive alignment across engineering, data, and business teams.
- Use experience and knowledge of all job areas within a function, practical experience in several functional areas or businesses, or concentrated knowledge of a particular discipline to coach and guide others.
- Lead by example and model behaviors that are consistent with CBRE RISE values. Negotiates with senior management, customers, regulators, or vendors to influence decisions of strategic importance. Anticipate potential objections, and persuade others, often at senior levels and of divergent interest, to adopt a different point of view.
- Drive the direction and resource allocation for programs, projects, or services.
- Significantly impact the design of policies and procedures. Provide moderate impact on the business direction through the development of innovative services or products., Pittsburgh, PA | Birmingham, AL | Cleveland, OH | Dallas, TX*Hybrid Planning Management Automation Governance Algorithms Data Mining Coordinating Data Science Risk Management Solution Design Data Processing Customer Service Business Process Machine Learning Unstructured Data Business Decisions Business Objectives Process Optimization Advanced Mathematics Workplace Inclusivity Artificial Intelligence Data-Driven Decision Making Swift (Programming Language) Enterprise Risk Management (ERM) Generative Artificial Intelligence +0
Google Advanced Data Analytics
Google Business Intelligence
Google Data Analytics
Google Project Management
Salesforce Developer Principal AI Engineer CBRE Richardson, TX*On-Site Sales CI/CD CrewAI LangChain Operations Leadership Consulting Management Innovation Communication Observability Mortgage Loans Responsible AI Microsoft Azure Trustworthiness Knowledge Graph Machine Learning Containerization Platform Mindset Edge Intelligence Project Management Influencing Skills Program Management Workflow Management Amazon Web Services Facility Management Resource Allocation Predictive Modeling Property Management Software Engineering Lifecycle Management Investment Management Commercial Real Estate Artificial Intelligence Real Estate Investments Concept Drift Detection Software Design Patterns Python (Programming Language) Generative Artificial Intelligence MLOps (Machine Learning Operations) Artificial Intelligence Infrastructure +0
Requirements
- Bachelor's or Master's Degree preferred with 10+ years of relevant experience in software and platforms engineering, with 5+ years of experience focused on AI/ML systems at enterprise scale. In lieu of a degree, a combination of experience and education will be considered.
- Proven track record building and scaling enterprise platforms with strong architectural and design pattern thinking.
- Hands-on experience across the AI stack - LLMs, generative AI, agentic frameworks (LangChain, CrewAI), knowledge graphs, and MLOps tooling.
- Strong Python proficiency and solid software engineering fundamentals.
- Experience with cloud platforms (Azure, AWS, GCP), containerization, and CI/CD pipelines.
- Strong communication and leadership skills with ability to influence executive audiences.