AI Solutions Engineer

Job Description Chatham Financial is looking for an AI Solutions Engineer to design, build, and deploy custom AI solutions that address high-value business workflows. This hybrid technologist and trusted advisor role requires working closely with stakeholders to understand operational challenges and build AI-powered solutions that create measurable value. The engineer will own problems end-to-end—from discovery through production. What You'll Do Client Engagement Work directly with private equity firms, real estate investors, and capital markets clients to understand their workflows and identify AI opportunities Lead discovery conversations to uncover pain points and scope solutions 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 vs. traditional ML vs. rule-based approaches Design systems that integrate with existing client infrastructure Hands-On Building Write production code - Python, modern web frameworks, LLM integrations (OpenAI, Anthropic, etc.) Build RAG systems, agentic workflows, and custom AI applications Own the full stack from data ingestion to user interface Rapid Prototyping Build working prototypes in days/weeks, not months Validate value quickly with real users and real data Iterate based on feedback and measured outcomes Production Deployment Take solutions from prototype to production Ensure reliability, security, and maintainability Support ongoing optimization and enhancement Contributors to Your Success 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 - can explain technical concepts to executives and collaborate with non-technical stakeholders Comfortable with ambiguity - can 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 early engineer) or consulting firm Experience with data pipelines, ETL, and working with messy enterprise data Familiarity with cloud platforms (AWS, Azure, GCP) Experience with vector databases, embeddings, and semantic search For New York based candidates, the compensation range for the position is expected to be between $200,000 and $275,000 annually. Total compensation, including base pay, discretionary individual bonus and company bonus, may be higher than range listed, depending on applicant's skills, qualifications, and experience. Benefits include health insurance, life and disability insurance, 401(k), EAP, paid holidays and paid time off. #J-18808-Ljbffr