Harrison Street is seeking to hire an AI Engineer within the Innovation Department, reporting to the Chief Innovation Officer. This individual will be instrumental in designing, building, and deploying AI/ML systems that further enhance the Firm’s AI strategy.
Responsibilities:
AI/ML Development & Deployment
- Design, develop, and deploy production-grade machine learning models to further enhance decision making
- Build and maintain Retrieval-Augmented Generation (RAG) architectures, agentic AI workflows, and multi-model orchestration pipelines to surface insights from structured and unstructured data
- Develop AI tools that translate model outputs into human-readable insights
Data Engineering & Infrastructure
- Build and optimize data pipelines to ingest, clean, and structure proprietary datasets across the Firm's investment portfolio
- Work within secure infrastructure to deploy scalable, secure AI solutions
- Integrate AI models with existing Firm systems, databases, and reporting workflows
Cross-Functional Collaboration
- Partner with investment, asset management, portfolio management, and Impact teams to identify AI use cases and translate business needs into technical solutions
- Facilitate innovation workshops, design thinking sessions, and prototype demonstrations for senior leadership
- Expand existing relationships with external partners, startups, and research institutions as appropriate to advance the Firm's AI capabilities
Responsible AI & Governance
- Ensure all AI systems are designed with human-in-the-loop principles
- Adhere to the Firm's AI Policy, including data access controls, bias mitigation, explainability standards, and regulatory compliance
- Build guardrails around AI scope, data access, and output reliability
Requirements:
- Bachelor's degree in Computer Science, Machine Learning, Data Science, Mathematics, Physics, or a related quantitative field
- 3–7 years of professional experience in AI/ML engineering or a closely related role
- Hands-on experience with LLMs and Generative AI, including RAG, prompt engineering, embeddings, fine-tuning, and agentic frameworks
- Experience with cloud platforms
- Strong data engineering skills
- Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders
Preferred
- Master's degree or PhD in a relevant field
- Prior experience in financial services, investment management, or real estate understanding of deal execution, due diligence, underwriting, and portfolio analytics
- Experience building and deploying AI systems in regulated environments
Competencies
- Translational Thinking - Ability to bridge AI capabilities and investment decision-making, making models actionable
- Human-Centered Design - Commitment to building AI systems that augment rather than replace human judgment
- Intellectual Curiosity - Passion for staying current with emerging AI technologies, industry trends, and competitive developments
- Ownership & Execution - Ability to lead projects from concept through production with minimal supervision