AI Engineering Lead — Onsite NYC, Hyper-Growth Fintech

Quantbase Investments, Inc.; New York, Northern (NY, KY); Hybrid; USD 170,000 - 250,000; Full time

Benefits offered by this job

401k (100% match up to 6%)

Healthcare

Dental

Job summary

Quantbase Investments, Inc. is seeking an AI Engineering Lead to work onsite in New York, NY.

You will partner with the founding team to design and build our AI efforts, owning the Hadrius platform from architecture to deployment, with a team-oriented, fast-paced startup culture emphasizing autonomy and impact. You will contribute across the AI stack, mentoring engineers, scaling AI capabilities for clients, and delivering production-ready backend Python code with minimal meetings and broad

Qualifications

• 6+ years of engineering experience.
• Built and deployed agentic experiences, owning everything from logging, labeling, evals and the like, end to end.
• Clear communicator with a penchant for solving problems.
• Previous experience in a fast-paced startup environment.
• Bachelor's or Master's degree in Computer Science or a related field.

Responsibilities

• Push your first PR to production in week one.
• Understand core problems Hadrius solves, ICP, value proposition, pricing structure, and roadmap.
• Learn the Hadrius way: how we work and build for hyper growth.
• Own the AI architecture for the entire Hadrius product.
• Pioneer and guide AI efforts; scale with clients and hire/mentor new team members.

Skills

6+ years engineering experience

Agentic experiences deployment

Clear communicator

Startup environment experience

Education

Bachelor's or Master's degree in Computer Science or related field

Job description

Quantbase Investments, Inc. is seeking an AI Engineering Lead to work onsite in New York, NY.

You will partner with the founding team to design and build our AI efforts, owning the Hadrius platform from architecture to deployment, with a team-oriented, fast-paced startup culture emphasizing autonomy and impact. You will contribute across the AI stack, mentoring engineers, scaling AI capabilities for clients, and delivering production-ready backend Python code with minimal meetings and broad