Forward Deployed Engineer

Description

As a Forward Deployed Engineer at Wonderful, you’ll turn complex enterprise workflows into AI agents that work in the real world.

You’ll operate at the intersection of engineering, product, and customer delivery. Embedding directly with enterprise teams, you’ll uncover how their operations actually run, identify where AI can create meaningful value, and build the systems that deliver it.

You’ll lead projects from initial discovery through production deployment, combining customer insight with hands-on engineering. After launch, you’ll measure real-world impact and keep iterating until the solution delivers meaningful results.

This role is for versatile engineers who enjoy combining deep technical work with customer context. You’re comfortable entering unfamiliar environments, asking incisive questions, and shipping practical solutions without waiting for a perfect specification.

Embed with customers to understand their workflows, constraints, and measures of success.

Turn loosely defined operational problems into clear technical plans and production systems.

Design and build AI agents that integrate with customer tools, data, and business processes.

Own deployments from prototype through launch, monitoring, and continuous improvement.

Test with real-world data, measure business outcomes, and iterate based on evidence.

Make pragmatic tradeoffs across architecture, reliability, speed, and user experience.

Partner closely with Wonderful’s Product and Engineering teams to improve the core platform.

Turn lessons from individual deployments into reusable tools, patterns, and best practices.

Responsibilities

• As a Forward Deployed Engineer at Wonderful, you’ll turn complex enterprise workflows into AI agents that work in the real world.
• You’ll operate at the intersection of engineering, product, and customer delivery. Embedding directly with enterprise teams, you’ll uncover how their operations actually run, identify where AI can create meaningful value, and build the systems that deliver it.
• You’ll lead projects from initial discovery through production deployment, combining customer insight with hands-on engineering. After launch, you’ll measure real-world impact and keep iterating until the solution delivers meaningful results.
• This role is for versatile engineers who enjoy combining deep technical work with customer context. You’re comfortable entering unfamiliar environments, asking incisive questions, and shipping practical solutions without waiting for a perfect specification.
• Embed with customers to understand their workflows, constraints, and measures of success.
• Turn loosely defined operational problems into clear technical plans and production systems.
• Design and build AI agents that integrate with customer tools, data, and business processes.
• Own deployments from prototype through launch, monitoring, and continuous improvement.
• Test with real-world data, measure business outcomes, and iterate based on evidence.
• Make pragmatic tradeoffs across architecture, reliability, speed, and user experience.
• Partner closely with Wonderful’s Product and Engineering teams to improve the core platform.
• Turn lessons from individual deployments into reusable tools, patterns, and best practices.

Requirements

• 5+ years of experience building software or solving complex technical problems.
• Strong foundations in software architecture, system design, and production engineering.
• Experience working across APIs, integrations, data flows, and distributed systems.
• The ability to bring structure and momentum to ambiguous problems.
• Confidence working directly with customers, from operational teams to technical stakeholders.
• Clear communication, sound judgment, and a strong sense of ownership.
• Genuine curiosity about applied AI and its potential to transform how businesses operate.
• Experience in a forward-deployed, solutions engineering, consulting, or customer-facing technical role.
• Experience building AI agents, workflow automation, or conversational systems.
• Familiarity with LLM evaluation, observability, and reliability in production.
• Experience deploying and improving systems in complex enterprise environments.