AI Solutions Engineer

Overview Chatham Financial is a leading independent capital markets advisor that empowers employees through professional development and delivers technology‑driven advisory services. This AI Solutions Engineer role focuses on designing, building, and deploying custom AI solutions that enhance high‑value business workflows across private equity, real estate, and capital markets. What You’ll Do Client Engagement – Work directly with private equity firms, real estate investors, and capital‑markets clients to understand workflows, identify AI opportunities, lead discovery conversations, scope solutions, and present recommendations to both technical and executive stakeholders. Solution Design & Architecture – Architect custom AI solutions including workflow automation, data extraction, intelligent reporting, and AI agents; evaluate when to use LLMs versus traditional ML or rule‑based approaches; design systems that integrate with existing client infrastructure. Hands‑On Building – Write production code in Python, modern web frameworks, and integrate LLMs (OpenAI, Anthropic). Build RAG systems, agentic workflows, and custom AI applications; own the full stack from data ingestion to user interface. Rapid Prototyping – Develop working prototypes in days or weeks, validate value quickly with real users and data, and iterate based on feedback and outcomes. Production Deployment – Transition prototypes to production, ensuring reliability, security, and maintainability; support ongoing optimization and enhancement. Qualifications 7+ years of software engineering experience, ideally with client‑facing or consulting exposure. Strong programming skills in Python; experience with TypeScript/JavaScript a plus. Hands‑on experience building with LLMs (GPT, Claude, etc.)—RAG, prompt engineering, fine‑tuning, or agentic systems. Experience taking AI/ML projects from prototype to production. Excellent communication skills—able to explain technical concepts to executives and collaborate with non‑technical stakeholders. Comfortable with ambiguity—able to scope problems, make decisions, and own outcomes end‑to‑end. Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent experience. Experience in financial services, private equity, or real estate. Background at a startup (especially as an early engineer) or consulting firm. Experience with data pipelines, ETL, and messy enterprise data. Familiarity with cloud platforms (AWS, Azure, GCP). Experience with vector databases, embeddings, and semantic search. Compensation and Benefits For NewYork‑based candidates, the salary range is $200,000–$275,000 annually, with potential for higher total compensation based on qualifications. Benefits include health, life, and disability insurance; 401(k); employee assistance program; paid holidays and paid time off. #J-18808-Ljbffr