AI Systems Builder

Hearst•New York, NY

10d

About The Position

Advances in AI tooling are fundamentally changing how software and systems are built. A single experienced builder can now design and deploy systems that previously required entire teams. At Hearst, we are building a team of AI Systems Builders who use modern AI development environments to turn ideas into working systems quickly. This role sits at the intersection of product thinking, software systems, and applied AI. You will take ambiguous problems and transform them into working AI-powered workflows, prototypes, and internal products used by teams across the company. This is not a traditional engineering role centered on writing large amounts of code manually. Instead, you will design systems, orchestrate AI tools and agents, and rapidly ship solutions that deliver real business impact. If you enjoy turning messy real-world problems into working systems that people actually use, this role may be a great fit.

Requirements

5+ years building technical systems or products
Strong understanding of modern software architecture (APIs, databases, cloud infrastructure)
Experience using AI tools, LLM APIs, or workflow automation platforms
The ability to review and reason about generated code and system behavior
Comfort working in ambiguous environments where problems are not fully specified

Nice To Haves

Focus on solving real problems, not just building demos
Move quickly from idea to working prototype
Understand how systems fit together and where they fail
Engage directly with stakeholders to understand real workflows
Care about delivering measurable outcomes and real adoption

Responsibilities

Design and ship AI-powered workflows, internal tools, and automation systems.
Translate business needs into system architectures and validation plans.
Rapidly prototype solutions and evolve them into durable internal products.
Use AI agents to generate code, configuration, documentation, and tests while reviewing outputs carefully.
Build reusable workflow assets such as instructions, integrations, and evaluation frameworks.
Leverage multimodal AI capabilities including vision, audio, and video when useful.
Partner directly with business teams to identify opportunities for AI-driven transformation.
Ensure systems are reliable, governable, and maintainable.