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MelodyArc

Forward Deployed Engineer

Posted One Month Ago
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
Embed with enterprise customers to design, build, and deploy production-grade AI Operator solutions. Lead architecture and integrations, configure agentic workflows, deliver end-to-end implementations, troubleshoot and optimize deployments, and feed product roadmap with field insights.
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MelodyArc is building the orchestration layer for enterprise service work — where rules, people, and AI collaborate to get complex operations done reliably at scale. Our orchestration core (the Point Engine) enables teams to configure agentic AI Operators that execute work end-to-end while leveraging existing business logic and human-in-the-loop workflows.

Role Overview

A MelodyArc Forward Deployed Engineer (FDE) partners directly with customers to design, implement, and scale AI Operator solutions that solve real-world business problems. FDEs serve as the bridge between product, engineering, and customer teams, translating business requirements into technical architectures, integrating AI systems with enterprise data sources and workflows, and ensuring successful deployment and adoption. They work hands-on across solution design, implementation, troubleshooting, and optimization while providing strategic guidance to customers, gathering product feedback, and helping shape the evolution of the MelodyArc platform based on real-world use cases.

You embed directly with our most strategic enterprise customers to deliver the custom solutions that make exceptional outcomes possible — every case, every time — for the work AI can't do alone. You partner closely with Deployment Strategists, who own the what and the why of each engagement; you own the how — the integrations, complex configuration, and production engineering that land measurable value.

The Impact You Will Have

• Own the architecture: lead design decisions for secure, scalable solutions on the MelodyArc platform, aligned to both the customer's systems and our best practices.

• Build on the platform: configure and extend Points, Point Sets, and AI Operators, and compose them through the Point Engine into production workflows that route across rules, AI, humans, and systems in real time.

• Deliver end-to-end: ship production-grade solutions spanning data and system integration, AI Operator configuration, the Portal experience operators work in, and the Recordability that makes every step traceable by design.

• Build agentic features directly for clients: stand up the AI-powered automations that resolve real operational work, with human-in-the-loop where risk or complexity demands it.

• Immerse with customers: embed with customer teams — from frontline operators to executives — to understand the problem and prove measurable outcomes.

• Collaborate cross-functionally: partner with Deployment Strategists, Sales, and Product to ensure a seamless journey from pre-sales through production.

• Scale impact: contribute reusable accelerators, frameworks, and deployment patterns, and channel field feedback into the product roadmap.

Basic Qualifications

• 7+ years of professional experience in software development, AI system design, or data/solutions engineering.

• Strong full-stack engineering background, with proficiency in TypeScript/NodeJS and Python, plus SQL, and comfort across backend, frontend, and systems integration.

• Demonstrated ability to design, build, and deploy production-grade applications that combine data pipelines, AI/ML, and user-facing interfaces.

• Hands-on experience integrating AI APIs (e.g., Anthropic, OpenAI, Gemini) into real applications; experience using AI coding tools to accelerate delivery is a plus.

• Proven track record delivering technical solutions in enterprise environments that drove measurable outcomes.

• Excellent communication, able to engage stakeholders from engineers to C-level executives.

• Based in the United States with professional working proficiency in English.

Preferred Qualifications

• Experience deploying data or AI/ML products into production at named enterprise accounts.

• Familiarity with workflow/orchestration engines, rules- and policy-driven execution, event-driven systems, or agent frameworks.

• Experience building enterprise integrations (APIs, webhooks, authn/authz, data sync, auditability).

• Domain experience in customer service operations, supply chain, or other high-volume business-process operations.

• Secure SDLC practices aligned with SOC 2 Type II or similar; comfort across managed and self-hosted enterprise infrastructure.

• Prior founder, early-team, or top-tier consultancy experience.

Location

Remote (United States). Some travel to customer sites may be required.

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