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Forward Deployed Engineer

Recruiting From Scratch (RFS Group)
New York, New York
On-siteUSD 155,000 - 225,000 / year

About this role

Forward Deployed Engineer

New York, New York | Onsite

2 - 10 Years of Experience

Who is Recruiting from Scratch:

Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire.

Forward Deployed Engineer

Location

New York, NY

Fully onsite, 5 days per week.

Company Stage of Funding

Early-Stage / High-Growth AI Fintech Company

Office Type

On-site — 5 days per week

Candidates should be comfortable working fully in-office in New York City.

Salary

$155,000 – $225,000 Base

Base salary of $155,000 – $225,000 depending on experience.

Equity

0.1% – 0.7% Significant Equity

Visa

Open to visa transfers, including OPT and H-1B transfers.

Experience

  • 2+ years of experience in software engineering, forward-deployed engineering, solutions engineering, implementation engineering, or a similar technical customer-facing role.

  • Employment Type

  • Full-time

  • Hiring Count

  • Early / Growth Hiring

  • Company Description

  • This is a fast-growing AI fintech company building an AI-powered platform that automates consumer debt collection.

  • The company uses AI agents to automate the late-stage debt recovery process, helping creditors recover debts that cannot be resolved through traditional voluntary communications.

  • The platform operates across multiple stages of the recovery lifecycle, including asset research, pre-legal outreach, litigation, credit reporting, and enforcement actions such as garnishments and liens.

  • The company is an early-stage, high-growth startup that has scaled from zero to approximately $3.5M ARR in around 18 months and is focused on continuing that growth toward $10M ARR.

  • This role sits at the intersection of software engineering, AI agents, enterprise implementations, customer success, and technical problem-solving.

  • The ideal candidate is a technically strong engineer who is equally comfortable working directly with enterprise customers. They should be able to gather requirements, understand customer workflows, configure and build AI agent implementations, troubleshoot technical issues in real time, and own the implementation through successful production deployment.

  • This is not a traditional customer success or project management role. The Forward Deployed Engineer is expected to personally build, configure, debug, and improve technical implementations while maintaining direct relationships with customers.

  • The role requires strong ownership and autonomy. Engineers own the customer relationship directly, communicate with clients through email and recurring calls, and are accountable for getting customers live and delivering measurable ROI during the first month after launch.

  • What You Will Do

    1. Lead Enterprise Customer Implementations

  • Own end-to-end technical implementations for enterprise customers.

  • Gather technical and business requirements directly from customers.

  • Lead recurring implementation calls and guide customers through the deployment process.

  • Understand customer workflows, requirements, and operational constraints.

  • Translate customer requirements into technical implementation plans.

  • Coordinate implementation milestones and ensure customers progress toward launch.

  • Identify technical blockers and independently determine appropriate solutions.

  • Maintain clear communication with customers throughout the implementation lifecycle.

  • Take ownership from initial requirements gathering through production launch.

  • Ensure implementations are completed successfully and on schedule.

    1. Build & Configure AI Agent Implementations

  • Build and configure AI-powered agent implementations for enterprise customers.

  • Work on implementations ranging from straightforward configurations to complex technical deployments.

  • Customize AI agent behavior based on customer workflows and requirements.

  • Work with LLM-powered systems and voice AI.

  • Debug AI behavior and determine why agents are not handling specific scenarios correctly.

  • Make technical changes and improvements in real time during customer implementations.

  • Configure workflows, integrations, prompts, business logic, and technical parameters.

  • Test AI agents against real-world customer scenarios.

  • Continuously improve implementations based on customer feedback and production performance.

  • Balance customer-specific requirements with scalable technical solutions.

    1. Troubleshoot & Own Production Technical Issues

  • Monitor customer implementations after launch.

  • Diagnose technical and AI-related issues quickly.

  • Communicate directly with customers when issues arise.

  • Make technical fixes in real time when appropriate.

  • Investigate unexpected AI agent behavior.

  • Debug application, integration, data, and workflow issues.

  • Work across the technical stack to resolve customer problems.

  • Collaborate with internal engineering teams when deeper product changes are required.

  • Ensure production systems remain reliable and effective.

  • Use customer feedback and implementation learnings to improve the product.

    1. Own Customer Outcomes & ROI

  • Own the customer relationship from implementation through early production usage.

  • Serve as the primary technical point of contact for assigned customers.

  • Communicate directly with customers through email, calls, and technical working sessions.

  • Ensure customers successfully go live.

  • Track implementation progress and post-launch performance.

  • Help customers achieve meaningful ROI during the first month after launch.

  • Understand customer business objectives and connect technical implementation decisions to those objectives.

  • Proactively identify opportunities to improve customer outcomes.

  • Build trust with enterprise stakeholders through strong technical execution and communication.

  • Feed customer implementation learnings back into product and engineering decisions.

  • Ideal Candidate Background

  • Experience Requirements

  • 2+ years of software engineering experience.

  • Experience building and deploying production software.

  • Experience working directly with customers, clients, users, or business stakeholders.

  • Experience owning technical implementations or customer-facing engineering projects.

  • Experience translating customer requirements into technical solutions.

  • Experience debugging and troubleshooting production systems.

  • Experience working in fast-moving startup or high-growth environments.

  • Experience working with AI-powered products is highly valuable.

  • Experience with enterprise implementations, solutions engineering, forward-deployed engineering, or technical consulting is a strong plus.

  • Experience owning projects independently from requirements through production.

  • Demonstrated ability to operate with significant technical and customer-facing autonomy.

  • Strong preference for candidates who have worked at early-stage startups or small engineering teams.

  • Technical Requirements

  • Strong software engineering fundamentals.

  • Strong TypeScript experience.

  • Experience with Node.js.

  • Experience building production web applications.

  • Experience with React.js.

  • Experience working with APIs and integrations.

  • Experience with SQL and relational databases.

  • Experience with AWS or cloud infrastructure.

  • Strong debugging and troubleshooting skills.

  • Ability to understand and modify existing production systems.

  • Ability to work across front-end and back-end systems when solving customer problems.

  • Strong understanding of application architecture.

  • Ability to make pragmatic technical tradeoffs.

  • Ability to quickly learn unfamiliar technical systems.

  • Strong production engineering judgment.

  • AI, LLM & Voice AI Requirements

  • Experience working with LLM-powered applications is highly valuable.

  • Experience with AI agents or agentic workflows is strongly preferred.

  • Familiarity with:

  • LLMs

  • GPT-based systems

  • Prompt engineering

  • AI agent configuration

  • Voice AI

  • Agent workflows

  • AI evaluation

  • AI debugging

  • Ability to diagnose and improve AI agent behavior.

  • Comfortable working with probabilistic AI systems where behavior may not always be deterministic.

  • Ability to translate business requirements into AI agent behavior.

  • Experience testing AI systems against real-world scenarios.

  • Strong understanding of the limitations and failure modes of LLM-powered systems.

  • Ability to balance AI performance, reliability, customer requirements, and implementation speed.

  • Customer & Implementation Requirements

  • Strong client-facing communication skills.

  • Comfortable leading recurring customer calls.

  • Comfortable gathering requirements directly from enterprise customers.

  • Strong presentation and technical communication skills.

  • Able to explain technical concepts to non-technical stakeholders.

  • Strong listening and questioning skills

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