Forward Deployed Engineer, AI Infrastructure & Impact

Fdetimes; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

Modal is seeking Forward Deployed Engineers to join our engineering team at the intersection of deep infrastructure work and direct customer impact. You will partner with leading AI companies on cloud architecture, storage, networking, and sandboxing to design and ship production infrastructure on Modal’s platform.

The team includes world-class engineers and researchers. You will work directly with customers on hard problems, shaping the platform and its adoption across major AI workloads.

Qualifications

• 3+ years of professional software engineering experience.
• Hands-on experience with cloud platforms (AWS, GCP, Azure).
• Experience with container orchestration (Docker, Kubernetes).
• Strong understanding of distributed systems and data pipelines.
• Excellent communication and ability to articulate tradeoffs to technical leadership.

Responsibilities

• Work hands-on with customers to architect and deploy production workloads on Modal.
• Lead technical discovery and architecture sessions with customers.
• Architect migration paths from existing cloud infrastructure to Modal’s serverless platform.
• Collaborate with product and sales teams, contributing as an engineer and product stakeholder.
• Build trusted relationships with technical leaders at customer companies.

Skills

3+ years software engineering

Distributed systems

Communication

Customer engagement

Tools

AWS

GCP

Azure

Docker

Kubernetes

Terraform

Pulumi

CloudFormation

Job description

Modal is seeking Forward Deployed Engineers to join our engineering team at the intersection of deep infrastructure work and direct customer impact. You will partner with leading AI companies on cloud architecture, storage, networking, and sandboxing to design and ship production infrastructure on Modal’s platform.

The team includes world-class engineers and researchers. You will work directly with customers on hard problems, shaping the platform and its adoption across major AI workloads.