Forward Deployed Engineer

Location

Flatiron, New York, NY

Fully onsite, 5 days per week.

Company Stage of Funding

Early-Stage / High-Growth AI Enterprise Software Company

Office Type

On-site — 5 days per week

Salary

$120,000 – $200,000 Base

Equity

Competitive Equity

Visa

Not open to visa sponsorship or visa transfers. US Citizens and Green Card holders only.

Experience

1–5 years of experience in software engineering, forward deployed engineering, solutions engineering, implementation engineering, or a similar customer-facing technical role.

Employment Type

Full-time

Hiring Count

Early / Growth Hiring

Company Description

This is an early-stage AI company building software for the home services industry, helping enterprise operators automate and improve critical workflows across scheduling, dispatch, customer communication, and technician management.

The company works with large home services businesses and is building AI agents that interact directly with customers through voice, text, and phone-based workflows. These systems are deployed into real operating environments where reliability, customer experience, and measurable business outcomes are critical.

As a Forward Deployed Engineer, you will sit at the intersection of engineering, product, and customers. You will work directly with enterprise customers, understand their operational challenges, build and deploy AI agent solutions, and feed real-world customer learnings back into the product organization.

This is a highly hands-on role for someone who enjoys both building software and working directly with customers. You will have significant ownership over implementations and will work closely with product, engineering, design, founders, and team leads to improve both individual customer outcomes and the broader platform.

What You Will Do

1. Build & Deploy AI Agent Solutions

• Build, configure, test, and deploy AI agents across voice, text, and phone-based customer workflows.
• Translate customer requirements and operational processes into reliable technical solutions.
• Work hands-on with APIs, integrations, data, LLMs, and production systems.
• Customize AI-powered workflows to address the unique needs of enterprise customers.
• Continuously improve agent performance based on customer feedback and real-world behavior.
• Use tools such as Python, TypeScript, Node.js, React, REST APIs, SQL, and modern AI frameworks to deliver solutions.

2. Own End-to-End Customer Implementations

• Serve as the primary technical point of contact throughout customer implementation and onboarding.
• Gather requirements directly from enterprise customers and understand their existing workflows.
• Lead technical implementation conversations and translate business requirements into executable solutions.
• Manage deployments from initial configuration through production launch.
• Troubleshoot technical issues and ensure customers are successfully using the product.
• Take ownership of post-sales implementation and ongoing technical success.

3. Partner Closely With Product, Engineering & Design

• Translate customer pain points and implementation learnings into actionable product feedback.
• Work cross-functionally with engineering, product, and design teams to improve the platform.
• Identify recurring customer problems that can be solved at the product level rather than through one-off implementations.
• Collaborate directly with founders and team leads on product roadmap decisions.
• Balance customer-specific requirements with scalable platform architecture.
• Help shape the evolution of AI-powered products based on real-world customer needs.

4. Drive Customer Success & Business Impact

• Build trusted relationships with enterprise customers and understand their business goals.
• Ensure customers see meaningful value from AI deployments.
• Monitor implementations after launch and proactively identify opportunities for improvement.
• Help drive customer satisfaction, retention, and account expansion.
• Communicate clearly with both technical and non-technical stakeholders.
• Take full ownership of customer outcomes rather than simply completing technical tasks.

Ideal Candidate Background

Experience Requirements

• 1–5 years of professional experience in software engineering, forward deployed engineering, solutions engineering, implementation engineering, or a similar role.
• Experience working directly with customers or external stakeholders.
• Experience building and deploying production software.
• Experience working in a startup, high-growth company, or environment with significant ownership.
• Demonstrated ability to take ambiguous requirements and turn them into working technical solutions.
• Experience owning projects or implementations from requirements gathering through deployment.

Technical Requirements

• Strong programming ability in at least one modern language, ideally Python or TypeScript.
• Strong experience with TypeScript and/or Node.js.
• Experience building applications with React.
• Experience working with REST APIs and third-party integrations.
• Strong SQL and database fundamentals.
• Experience working with cloud infrastructure, ideally AWS.
• Strong debugging and troubleshooting skills.
• Ability to understand existing systems and quickly make production changes.
• Experience working with tools such as Postman and API development/debugging workflows.

AI, LLM & Agent Requirements

• Hands-on experience building or deploying AI/LLM-powered applications.
• Understanding of LLM APIs, prompting, structured outputs, tool/function calling, or agentic workflows.
• Experience working with AI agents in production is highly valuable.
• Familiarity with frameworks such as LangChain or similar AI application frameworks.
• Experience with voice AI, conversational AI, or text-based AI systems is a strong plus.
• Ability to evaluate AI behavior and troubleshoot failures in real-world customer scenarios.
• Interest in rapidly evolving AI technologies and practical application of LLMs.

Customer & Implementation Requirements

• Strong experience working directly with customers or enterprise stakeholders.
• Ability to gather requirements and translate business problems into technical solutions.
• Comfortable leading implementation calls, technical discussions, and customer meetings.
• Experience with onboarding, integrations, deployments, or post-sales technical implementations.
• Strong written and verbal communication.
• Ability to troubleshoot issues with customers in real time.
• Comfortable balancing customer-specific requests with scalable product decisions.
• Experience working with enterprise systems or platforms such as CRM, field-service, or workflow software is a plus.

Soft Skills

• Exceptional ownership and accountability.
• Strong customer empathy.
• Clear and confident communicator.
• Comfortable working directly with senior customer stakeholders.
• Highly adaptable and comfortable with ambiguity.
• Strong problem-solving and debugging mindset.
• Able to move quickly without sacrificing technical quality.
• Comfortable operating across engineering, product, and customer-facing responsibilities.
• High attention to detail.
• Strong startup mentality and willingness to take on responsibilities beyond a narrow job description.

Compensation & Benefits

• $120,000 – $200,000 base salary.
• Competitive equity.
• Unlimited PTO.
• $0-cost medical insurance.
• 401(k) matching.
• Lunch and dinner provided in the office.
• Gym membership stipend.
• Clear Travel Pass.
• Technology equipment of your choice.
• Relocation assistance.
• Fully onsite in Flatiron, New York City.

Why Join

• Build and deploy AI agents that directly impact real enterprise businesses.
• Work closely with large home services operators and solve meaningful operational problems.
• Combine software engineering with customer-facing ownership.
• Work directly with founders, product, engineering, and design.
• Have a direct influence on the product roadmap.
• Operate in a small, high-growth team where individual contributions have significant impact.
• Gain deep exposure to production AI, enterprise implementations, and customer-driven product development.
• Work on AI systems where performance and reliability have measurable business outcomes.