Forward Deploy Engineer NYC

Breakmark•New York, NY

2d•Hybrid

About The Position

Build AI agents that move beyond experimentation and into the day-to-day operations of major enterprises. Whether you’re already working with agentic AI or are an experienced software engineer ready to focus on it, this role offers the opportunity to take systems from initial discovery through to production—and see the impact of what you build. You’ll join the founding team in New York City at an ambitious global AI company, working directly with enterprise customers to solve complex operational problems. Delivery happens in weeks and months, with real ownership of the technical decisions, implementation, and outcomes.

Requirements

Several years of professional software engineering experience.
A track record of building and scaling end-to-end production systems.
Experience integrating software with customer systems, APIs, cloud infrastructure, and production data flows.
Strong technical judgment and a practical approach to solving complex problems.
Confidence working directly with customers and bringing structure to ambiguous requirements.
Clear communication, initiative, and ownership from initial design through delivery.
A strong interest in building reliable AI-powered systems that deliver measurable value.

Nice To Haves

Experience in forward deployed engineering, solutions engineering, or another customer-facing technical role.
Experience with AI agents, MCP, automation, or conversational systems.
Proficiency in TypeScript, Go, or Python.
Experience working in a fast-growing startup.

Responsibilities

Work directly with customers to understand their operations, technical environments, and success criteria.
Turn open-ended business problems into clear technical designs and working systems.
Build and deploy AI agents that connect to customer systems, data sources, and APIs.
Write production-quality code for integrations, business logic, and workflows.
Own implementations from discovery through launch, including testing, reliability, and performance.
Run technical workshops and guide customer teams on implementation best practices.
Test against real operational data, measure results, and iterate quickly.
Partner with Product and Engineering to improve the platform based on what you learn in the field.
Develop reusable tools, documentation, and delivery practices that help the team scale.