Forward-Deployed AI Engineer for Advisor Workflows

Morningstar; Chicago (IL); Hybrid; USD 85,000 - 144,510; Full time

Benefits offered by this job

401(k) match up to 6%

Stock ownership potential

Company-provided life insurance

Comprehensive health benefits

HSA contributions

6-week sabbatical program

Parental leave and education stipend

Job summary

Morningstar, based in Chicago, is seeking Forward‑Deployed AI Engineers to rapidly prototype AI solutions within real‑world advisor workflows. This hybrid role collaborates with product managers, UX designers, and researchers to turn ideas into functioning prototypes with swift feasibility validation.

Success is measured by fast, evidence‑based prototypes that can move downstream, with downstream production engineers able to operationalize them with minimal friction.

Qualifications

• 1–2 years of AI engineering experience.
• Experience using AI coding tools like Claude Code and/or Cursor.
• Experience with Python, LLMs, prompt engineering, and AI frameworks.
• Ability to rapidly prototype with limited infrastructure.
• Strong problem‑solving and communication skills.

Responsibilities

• Build and iterate AI prototypes for advisor workflows.
• Integrate signals, models, and UX designs into working experiments.
• Test feasibility and performance of AI behaviors in real workflows.
• Collaborate with PMs, UX designers, and Research & Signals Lead.
• Capture technical learnings and provide handoff documentation for production teams.
• Rapidly validate ideas before long‑term engineering investment.

Skills

AI prototyping

Data integration

Cross-functional collaboration

Experimentation

Technical documentation

Tools

Claude Code

Cursor

Job description

Morningstar, based in Chicago, is seeking Forward‑Deployed AI Engineers to rapidly prototype AI solutions within real‑world advisor workflows. This hybrid role collaborates with product managers, UX designers, and researchers to turn ideas into functioning prototypes with swift feasibility validation.

Success is measured by fast, evidence‑based prototypes that can move downstream, with downstream production engineers able to operationalize them with minimal friction.