Forward Deployed Engineer

Morpheus Talent Solutions; New York (NY); On-site; USD 140,000 - 180,000; Full time

Job summary

Morpheus Talent Solutions is seeking a Forward Deployed Engineer to deploy and operate AI systems for enterprise customers across logistics, manufacturing, construction, and energy. You’ll own production success, ensuring reliability, integration, and measurable business value.

In this non-traditional software role, you’ll work with operations teams, translate feedback into product improvements, and integrate AI agents with ERP/CRM/WMS/TMS and other systems.

Qualifications

• Experience deploying AI solutions within enterprise or operational environments (logistics, manufacturing, energy, or similar).
• A strong full-stack engineer capable of owning production systems end-to-end.
• Ability to work directly with customers and translate operational challenges into technical solutions.
• Owns ownership, moves quickly, and thrives in ambiguous environments.
• Hands-on experience with modern LLMs, AI agents, and production AI systems.
• Experience in forward-deployed, solutions, or customer engineering roles.
• Familiarity with model evaluation, monitoring, and fine-tuning workflows.

Responsibilities

• Own the reliability, performance, and uptime of production AI systems.
• Monitor and improve model quality, accuracy, and operational performance.
• Build and maintain integrations with ERP, CRM, WMS, TMS, and other systems.
• Work with operations teams to translate workflows into product improvements.
• Diagnose production issues, optimize system behavior, and expand platform capabilities.
• Ensure AI systems continue delivering measurable outcomes for customers.

Skills

Full-stack engineering

Customer-facing collaboration

Production systems ownership

Tools

TypeScript

Python

React

Tailwind CSS

Cloud infrastructure

Authentication platforms

Workflow orchestration tools

Job description

We're hiring a Forward Deployed Engineer to help deploy and operate AI systems that solve real operational problems for enterprise customers in industries like logistics, manufacturing, construction, and energy.

This isn't a traditional software engineering role. The AI platform automatically deploys customer-specific operators—your job begins once they're live. You'll own their success in production, ensuring they're reliable, well-integrated, continuously improving, and delivering measurable business value.

What you'll do:

• Own the reliability, performance, and uptime of production AI systems.
• Monitor and improve model quality, accuracy, and operational performance.
• Build and maintain integrations with enterprise platforms such as ERP, CRM, WMS, TMS, and other operational systems.
• Work directly with operations teams and business stakeholders to understand workflows and translate feedback into product improvements.
• Diagnose production issues, optimize system behavior, and expand platform capabilities as customer needs evolve.
• Ensure AI systems continue delivering the outcomes customers depend on.

Technical environment - You'll work across a modern AI platform that includes:

• Dedicated inference infrastructure with customer-specific models.
• Config-driven AI agents that can be updated without code deployments.
• Multi-agent orchestration and workflow automation.
• Model evaluation, monitoring, observability, and guardrail systems.

Core technologies: TypeScript, Python, React, Tailwind CSS, modern cloud infrastructure, authentication platforms, and workflow orchestration tools.

We're looking for someone who:

• Has experience deploying AI solutions within enterprise or operational environments (logistics, manufacturing, supply chain, energy, or similar).
• Is a strong full-stack engineer comfortable owning production systems end-to-end.
• Enjoys working directly with customers and translating operational challenges into technical solutions.
• Takes ownership, moves quickly, and thrives in ambiguous environments.
• Has hands-on experience with modern LLMs, AI agents, and production AI systems.
• Experience in forward-deployed, solutions, or customer engineering roles.
• Familiarity with model evaluation, monitoring, and fine-tuning workflows.

This is an opportunity to work closely with customers, solve complex real-world problems, and help shape the future of AI in enterprise operations.