Forward Deployed Engineer – Applied AI and Automation

Our client is seeking a Forward Deployed Engineer with 5–10 years of experience to embed directly within acquired engineering businesses, own the full journey from user discovery to shipped software, and build the relationships that make AI adoption successful.

This is a true forward-deployed engineering role—not solutions architecture, software configuration, or ticket-based implementation. You will work directly with users, identify high-value problems, decide what should be built, write production code, deploy solutions, and iterate with users in real time.

The company is specifically looking for a senior engineer who can independently lead complex projects and help strengthen a growing, high-potential engineering team.

What You’ll Do

Embed on-site at acquired engineering firms and work directly beside employees.

Earn the trust of technical and non-technical users.

Identify the highest-value workflows to automate.

Own discovery, development, production deployment, debugging, and live iteration.

Translate unclear user pain and noisy feedback into strong product decisions.

Run working sessions and own user relationships end-to-end.

Independently identify opportunities to expand the scope and impact of a deployment.

Apply lessons from individual deployments to a shared technology platform.

Help lead complex projects and support the development of less experienced engineers.

Required Qualifications

5–10 years of relevant full-stack, forward-deployed, or customer-facing engineering experience.

Strong hands-on full-stack product engineering ability.

Proven experience writing, shipping, and owning production code.

Genuine forward-deployed experience with real users.

Experience personally owning discovery, development, production deployment, debugging, and iteration.

Strong product judgment and the ability to determine what should—and should not—be built.

Production experience with at least one of the following: LLMs, RAG, agent frameworks, or document parsing.

Ability to translate user feedback into clear product decisions and shipped solutions.

Ability to lead complex projects independently with limited structure or direction.

Strong English fluency and the communication skills needed to earn trust with non-technical users.

Comfort operating in ambiguous, zero-to-one environments.

At least one strong background signal:

Recognizable early-stage startup experience at approximately Seed through Series C, or

Top-tier technical education

Alignment with at least one target profile:

Founding or early engineer at a VC-backed startup with significant product ownership, or

True Forward Deployed Engineer with hands-on product-building experience

Willingness to work from the NYC office 5 days per week.

What True Forward Deployed Experience Means

Strong candidates have personally:

Worked directly with users to discover problems.

Formed an opinion about what should be built.

Made product and technical decisions.

Written and owned production code.

Deployed software into a real customer environment.

Debugged production issues.

Gathered feedback and improved the solution after launch.

An FDE title alone is not enough. Solutions architecture, platform configuration, implementation support, or technical consulting without substantial product engineering does not meet the requirement.

Ideal Background

Strong candidates may have:

Founder, founding engineer, or early-stage engineering experience.

Experience at a high-growth, top-tier VC-backed startup.

Forward-deployed engineering experience at an enterprise software or AI company.

Significant ownership over products and technical decisions.

Experience deploying applied AI into real customer workflows.

Strong entrepreneurial instincts or ambitions to eventually start a company.

Experience coaching junior engineers or providing technical leadership.

A record of working independently without detailed specifications or a predefined roadmap.

Deep curiosity, low ego, strong communication, and a hunger to solve real user problems.

The engineering environment includes technologies and concepts such as:

Next.js

Vercel

Tailwind CSS

Kotlin

Python

AWS

Pulumi

LLMs

RAG

Agent frameworks

LangChain

LlamaIndex

OpenAI APIs

Document parsing

Browser automation

Industry-specific software integrations

Candidates are not required to have used every technology listed. Production experience with LLMs, RAG, agent frameworks, or d…