Forward Deployed Engineer

Harrison Clarke; Seattle (WA); On-site; USD 270,000 - 330,000; Full time

Benefits offered by this job

Early-stage equity

Job summary

Harrison Clarke partners with a GenAI infrastructure leader to recruit a Customer Success Engineer / Forward Deployed Engineer embedded with enterprise clients. You will bridge engineering and customer teams, scoping implementations, building integrations, and solving complex deployment challenges from day one.

Based in Seattle, WA, you will own the full lifecycle from onboarding to expansion, working with modern GenAI stacks and cloud providers to ensure maximum value and ROI for customers.

Qualifications

• 3–7+ years in software engineering, solutions engineering, forward deployed engineering, or technical customer success at a SaaS or developer tools company.
• Strong programming skills in Python and/or TypeScript — read customer codebases, write integration scripts, and prototype solutions on the fly.
• Familiarity with the modern GenAI stack: LLM APIs (OpenAI, Anthropic, Azure OpenAI, Bedrock), orchestration frameworks, and cloud platforms (AWS, Azure, GCP).

Responsibilities

• Lead technical deployment of the platform across enterprise GenAI stacks — integrating with LLM providers, orchestration frameworks, and internal data pipelines to instrument cost, usage, and ROI telemetry.
• Scope custom implementations, design integration architectures, and build proof-of-value deployments tied to customer KPIs and business outcomes.
• Serve as frontline technical expert for enterprise accounts — debugging integration issues, optimizing platform performance, and solving deployment challenges.
• Translate customer patterns into actionable product requirements, feature requests, and roadmap input.
• Build docs, runbooks, and training materials to help customer teams self-serve and scale usage.
• Identify opportunities to deepen platform adoption within existing accounts and surface new GenAI initiatives.

Skills

Python

TypeScript

API debugging

Tools

OpenAI APIs

Azure OpenAI

LangChain

Semantic Kernel

AutoGen

Job description

Compensation: Up to $300,000 base + equity

About the Company

Our client, backed by multiple Tier 1 VC is a GenAI infrastructure company building the ROI intelligence platform for enterprise AI. Their technology connects every GenAI agent and use case to real financial outcomes, ROI traceability, unit-economics analytics, and capacity management, giving Product, Finance, and Engineering teams a single pane of glass across their entire AI portfolio.

Trusted by multiple Fortune 500 companies, the platform has already delivered a 47% ROI improvement and 86% reduction in waste spend for customers.

The Role

This is a Customer Success Engineer / Forward Deployed Engineer role, you'll be embedded with the company's most important enterprise customers, serving as the technical bridge between their engineering teams and the platform. You won't just support customers; you'll scope implementations, build integrations, solve hard technical problems on-site, and feed insights back to the product team. You're part engineer, part solutions architect, part trusted advisor.

The company's customers are deploying GenAI agents at scale across complex enterprise environments, Azure, AWS, multi-model stacks, provisioned capacity, agentic workflows. They need someone who can speak their language, get into their codebase, and ensure the platform delivers maximum value from day one. You'll own the full customer lifecycle from technical onboarding through expansion.

What You'll Do

• Customer Onboarding & Implementation: Lead the technical deployment of the platform across enterprise GenAI stacks — integrating with LLM providers, orchestration frameworks, and internal data pipelines to instrument cost, usage, and ROI telemetry.
• Solutions Engineering: Scope custom implementations, design integration architectures, and build proof-of-value deployments that tie directly to customer KPIs and business outcomes.
• Technical Troubleshooting: Serve as the frontline technical expert for enterprise accounts — debugging integration issues, optimising platform performance, and resolving complex deployment challenges.
• Product Feedback Loop: Act as the voice of the customer internally — translating patterns from the field into actionable product requirements, feature requests, and roadmap input.
• Enablement & Training: Build documentation, runbooks, and training materials that help customer teams self-serve and scale their usage across business units.
• Expansion & Advocacy: Identify opportunities to deepen platform adoption within existing accounts — surfacing new use cases, teams, and GenAI initiatives that the platform can instrument.

Who You Are

• You're a technical problem-solver who thrives in customer-facing environments. You're equally comfortable whiteboarding architecture with a VP of Engineering and debugging API calls in a terminal.
• 3–7+ years in software engineering, solutions engineering, forward deployed engineering, or technical customer success at a SaaS or developer tools company.
• Strong programming skills in Python and/or TypeScript — you can read customer codebases, write integration scripts, and prototype solutions on the fly.
• Familiarity with the modern GenAI stack: LLM APIs (OpenAI, Anthropic, Azure OpenAI, Bedrock), orchestration frameworks (LangChain, Semantic Kernel, AutoGen), and cloud platforms (AWS, Azure, GCP).
• Understanding of enterprise software economics — cost attribution, unit economics, usage-based pricing, and how finance teams think about technology ROI.
• Excellent written and verbal communication — you can translate deeply technical concepts for non-technical stakeholders and write clear documentation.
• Comfortable working autonomously in a fast-moving, early-stage environment (~13 people). You'll be one of the first customer-facing technical hires.

What's on Offer

• Early-stage equity in a company tackling one of the biggest unsolved problems in enterprise AI — proving GenAI ROI.
• Work directly with enterprise customers at major cloud providers, global consultancies, and Fortune 500 companies deploying GenAI at scale.
• Greenfield role, you'll define how the customer success engineering function works from the ground up.
• A founding team with deep enterprise AI and cloud platform experience.