AI Product Builder, AssociateYou Will:Product Contribution & Learning- Analyze private markets workflows and user behavior to identify high-impact problems worth solving.
- Synthesize client feedback, usage signals, and business context into clear product hypotheses and feature definitions.
- Contribute to roadmap definition, feature scoping, and prioritization alongside senior PMs and engineers.
- Influence product decisions through evidence, judgment, and execution quality.
AI Product Development- Use hands-on technical work to validate product ideas and de-risk delivery.
- Design, implement, and iterate on AI-powered product features where engineering is required to prove value.
- Build and refine LLM prompts, pipelines, and workflows that surface insights and perform tasks.
- Collaborate closely with engineers to take validated concepts into production.
- Monitor AI skill quality signals across clients and channels; tune prompts, adjust data
- contexts, and validate improvements using structured evaluation approaches.
Delivery, Communication & Feedback- Help produce documentation, release notes, and demos that explain what was built and why.
- Support internal teams (product, engineering, client success) in understanding and deploying new features.
- Occasionally engage directly with clients or end users to understand real-world usage and pain points.
Your scope will expand as you demonstrate judgment, execution quality, and reliability.
You Have:- Early-career engineer or technical product builder (internships, projects, or 1-3 years
experience). - Hands-on exposure to LLMs, generative AI, prompt engineering, agent development
- Curiosity about product delivery, not just model behavior.
- Ability to explain technical and product concepts clearly to different audiences.
- Technical fundamentals (i.e. Python, Go, SQL).
- Interest in private markets, fintech, or complex B2B workflows (experience is a plus, not
a requirement).
Tech Stack & Tools (nice to haves)- Languages / Tools: Python, Go, SQL, Pandas, Git, shell
- Platforms: Investorflow Proprietary AI Platform + Snowflake, Salesforce, LLM API (Anthropic, OpenAI, and others), MCP-compatible integrations
- Infrastructure: Kubernetes (basic familiarity), data pipelines, ETL
- Product: Github, Jira, Productboard
$105,000 - $115,000 a year