Forward Deployed Engineer (m/f/d)

zvoove; United States; Hybrid; USD 140,000 - 210,000; Full time

Job summary

zvoove is seeking a forward deployed engineer to join an AI Product Builder, embedding with customers to shape requirements and implement them—directly or via coding agents. You will own the technical outcome of a major feature area across product, engineering, and AI delivery.

Responsibilities include turning intent into specs for agents, coordinating delivery, and balancing AI-driven work with deterministic system behavior.

Qualifications

• Strong interest and hands-on experience with AI tools such as Claude, Cursor, and MCP, different LLM models, and prompting techniques.
• Proficiency in TypeScript or another production language such as Python, Java, or C#.
• Proven ownership of a feature area or product slice, having decided implementation and architecture from the problem rather than from a ticket.
• Fluency directing AI coding agents: writing specs and acceptance criteria, supervising execution, and rejecting output that is not production-ready.
• Enough product and customer judgement to challenge specs, a personal standard for code quality including on AI‑generated code, and comfort working with product, engineering, and governance counterparts without waiting for a perfect brief.
• Fluent German at C1 level and English at B2 level.

Responsibilities

• Own a product or major feature area end to end: discovery, implementation, quality, and delivery.
• Turn intent into precise specifications that coding agents can execute, then orchestrate and review their output.
• Decide where AI judgement is acceptable and where the system must stay deterministic, judging work on outcomes and tests rather than cleverness.
• Co-design solutions with the AI Product Builder as a near-peer, pushing back on specs that are clear but wrong.
• Identify and assess AI use cases on value, feasibility, and risk, and design evaluation for AI-delivered work covering test cases, inconsistency, hallucination, and bias.
• Raise responsible‑AI, privacy, and regulatory concerns early, and work with engineering on integration constraints so shipped work fits the systems it has to live in.

Skills

AI tooling

TypeScript

Python/Java/C#

Product ownership

Specification writing

German (C1)

English (B2)

Education

Degree in computer science

Tools

Claude

Cursor

MCP

Job description

Role overview

Forward deployed engineer embedded alongside an AI Product Builder, working shoulder-to-shoulder with customer problems to shape requirements and then implement them, both directly and through coding agents. The role sits at the intersection of product, engineering, and AI delivery, owning the technical outcome of an entire product or major feature area rather than just executing tickets.

Responsibilities

• Own a product or major feature area end to end: discovery, implementation, quality, and delivery.
• Turn intent into precise specifications that coding agents can execute, then orchestrate and review their output.
• Decide where AI judgement is acceptable and where the system must stay deterministic, judging work on outcomes and tests rather than cleverness.
• Co-design solutions with the AI Product Builder as a near-peer, pushing back on specs that are clear but wrong.
• Identify and assess AI use cases on value, feasibility, and risk, and design evaluation for AI-delivered work covering test cases, inconsistency, hallucination, and bias.
• Raise responsible‑AI, privacy, and regulatory concerns early, and work with engineering on integration constraints so shipped work fits the systems it has to live in.

Requirements

• Strong interest and hands-on experience with AI tools such as Claude, Cursor, and MCP, different LLM models, and prompting techniques.
• Proficiency in TypeScript or another production language such as Python, Java, or C#.
• Proven ownership of a feature area or product slice, having decided implementation and architecture from the problem rather than from a ticket.
• Fluency directing AI coding agents: writing specs and acceptance criteria, supervising execution, and rejecting output that is not production-ready.
• Enough product and customer judgement to challenge specs, a personal standard for code quality including on AI‑generated code, and comfort working with product, engineering, and governance counterparts without waiting for a perfect brief.
• Fluent German at C1 level and English at B2 level.

Nice to have

• Experience with RAG pipelines, agent frameworks, vector stores, or orchestration.
• A track record of cutting rework by making specs unambiguous before agents run.
• Familiarity with responsible‑AI practice and regulation relevant to production software in Europe, including the EU AI Act.
• Hands‑on evaluation of third‑party AI components or platforms.
• A degree in computer science or a related discipline.

Benefits and work setup

Work across AI-powered SaaS and cloud-native products using modern AI tooling daily. Empathetic, appreciative team culture with room to contribute ideas and take ownership, individual development opportunities, structured onboarding, interdisciplinary collaboration, flexible working models including hybrid, home office, and mobile work, and a modern agile tech environment.