Applied AI Engineer

Bandit Running•New York, NY

7h•$150,000 - $170,000

About The Position

Bandit Running is seeking an Applied AI Engineer to help build the systems that change how work gets done at Bandit. You’ll partner closely with our Head of Data & Technology to identify the largest opportunities across the business and turn them into production AI tools, agents, and automated decision loops. This is a hands-on builder role, not a research or advisory role. You’ll work across models, APIs, data, application logic, and deployment to take projects from problem → prototype → production system. Early use cases will span growth, marketing, and operations, with significant freedom to shape what we build and how we build it.

Requirements

4+ years of software engineering experience, with a track record of shipping production systems.
1+ years deeply immersed in applied LLM engineering—actively following, testing, and adopting the best techniques emerging from frontier model labs and the broader AI engineering community.
Hands-on experience building agents and LLM applications using tool calling, structured outputs, context/retrieval systems, evaluations, and multi-step workflows.
Strong across Python/TypeScript, APIs, SQL/databases, cloud infrastructure, and application deployment.
Strong product and business judgment—you can take an ambiguous problem, determine what should actually be built, and ship quickly without sacrificing reliability where it matters.
Comfortable operating broadly and independently across engineering, data, growth, creative, and operational problems.

Nice To Haves

Depth of traditional software engineering is helpful, but not required.

Responsibilities

Build production AI systems end-to-end — agents, internal applications, workflows, and decision systems that connect models with Bandit’s data and operational tools.
Design agent architecture and infrastructure — including tool use, permissions, context management, memory, triggers, scheduling, observability, and human-in-the-loop controls.
Automate growth and marketing workflows — starting with systems that evaluate performance, make recommendations, generate or iterate creative, and accelerate experimentation across paid media, CRM, and site merchandising.
Build personalization and decisioning systems that turn customer, product, membership, and behavioral signals into relevant actions and experiences.
Help define Bandit’s applied AI strategy by identifying where AI can materially increase team capacity, improve decision quality, or shorten the time between idea, experiment, and learning.