AI Product Engineer — End-to-End LLM Systems

Chris Baily; New York (NY); Hybrid; USD 91,000 - 254,000; Full time

Benefits offered by this job

Unlimited vacation policy

Monthly Phone Stipend

Medical, Dental, Vision insurance

401(K) plan with matching

Dog friendly office

Hybrid work opportunity

Professional Development Program

Seamless allowance

Job summary

WITHIN is seeking a Member of Technical Staff focused on AI to design applied AI systems and build products across frontend, backend, and data. You will own end-to-end product lifecycle, from problem definition to launch, evaluation, and maintenance, with a focus on LLM-powered applications and agent workflows.

The role emphasizes rapid iteration, collaboration with business teams, and scaling in production.

Qualifications

• Strong Python skills and experience building production systems.
• Experience with LLM APIs (OpenAI, Anthropic, Vertex AI).
• Experience building agent workflows that use tools, call external systems, maintain state, and handle multi‑step tasks.
• Experience designing evaluations for LLM-powered systems, including test cases, quality measures, regression testing, and review of production failures.
• Experience with SQL and integrating external APIs.
• Experience with GCP, AWS, or Azure.
• Ability to build product around AI components including frontend, backend, and data.

Responsibilities

• Own end‑to‑end AI product development lifecycle, from problem to launch to maintenance.
• Define the problem, scope, and development plan in collaboration with business partners.
• Ship AI products, evaluate results, and iterate for scale and reliability.

Skills

Strong Python skills

LLM APIs

Agent workflows

SQL

GCP

AWS

Azure

TypeScript

React

Backend services

Context management

Tools

OpenAI API

Anthropic API

Vertex AI

Job description

WITHIN is seeking a Member of Technical Staff focused on AI to design applied AI systems and build products across frontend, backend, and data. You will own end-to-end product lifecycle, from problem definition to launch, evaluation, and maintenance, with a focus on LLM-powered applications and agent workflows.

The role emphasizes rapid iteration, collaboration with business teams, and scaling in production.