5+ years in solutions engineering, sales engineering, or customer-facing technical roles
Hands-on experience with AWS, GCP, Azure cloud platforms
Strong knowledge of Docker, Kubernetes, and container orchestration
Experience with SQL/NoSQL databases and distributed systems architecture
Understanding of ML/AI infrastructure, including MLOps workflows
Familiarity with Infrastructure as Code and CI/CD pipelines
Proven track record of enterprise software sales cycles ($100K+ ACV)
Responsibilities
Collaborate with sales team to identify and close strategic enterprise opportunities
Lead technical discovery sessions to assess customer infrastructure and needs
Design and present tailored technical solutions for customer requirements
Architect migration strategies from existing cloud platforms to Modal
Conduct technical demonstrations and proof-of-concepts for prospective clients
Address technical evaluations, security, compliance, and integration concerns
Establish trusted relationships with technical decision-makers
Communicate customer feedback to product and engineering teams
Benefits
Opportunity to work with a rapidly growing AI infrastructure company
Chance to influence product development and company direction
Collaboration with a skilled and diverse team from top tech backgrounds
Professional growth opportunities in a fast-paced environment
Exposure to cutting-edge technology and innovation in AI and serverless computing
Travel opportunities for customer engagements and industry events
Full Job Description
The Role:
We're looking for Forward Deployed Engineers on our engineering team who want to work at the intersection of deep infrastructure work and direct customer impact. As an FDE, you'll partner with leading AI companies and foundation labs on cloud architecture, networking, storage, containerization, sandboxing, and more - helping them design and ship production infrastructure on Modal's platform.
The FDE team today includes world-class software engineers, computational scientists, ML engineers, and former founders. We're looking for people with strong engineering fundamentals, deep curiosity across the infrastructure stack, and energy for working directly with customers on hard problems. You will:
Work hands-on with companies like Suno, Lovable, Cognition, and Meta to architect and deploy massive-scale production workloads on Modal
Lead technical discovery and architecture sessions with prospective and existing customers
Architect migration paths from existing cloud infrastructure (AWS, GCP, Azure) to Modal's serverless platform
Collaborate with Modal's product and sales teams, contributing to the platform as both an engineer and a product stakeholder
Build trusted relationships with technical leaders (CTOs, VPs of Engineering, ML leads) at companies doing frontier AI work
Conduct technical demos, experiments, and proof-of-concepts that make Modal's infrastructure advantages tangible
Requirements:
3+ years of professional software engineering experience
Hands-on experience with cloud platforms (AWS, GCP, Azure) - compute, storage, networking, and container orchestration (Docker, Kubernetes)
Familiarity with distributed systems architecture, data pipelines, and Infrastructure as Code (Terraform, Pulumi, CloudFormation)
Strong communicator who can go deep on systems architecture with an infrastructure team and clearly articulate tradeoffs to technical leadership
Genuine interest in working directly with customers - you find it energizing to understand someone else's problem and help them solve it
Bonus: experience leading large-scale migration efforts, open-source contributions, or side projects you're proud of
Willing to work in-person in New York City, San Francisco, or Stockholm
