Forward Deployed Engineer - Systems
About Us:
Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference. Companies like Suno, Lovable, and Substack rely on Modal to move from prototype to production without the burden of managing infrastructure.
We're a fast-growing team based out of NYC, SF, and Stockholm. We've hit 9-figure ARR and recently raised a Series B at a $1.1B valuation. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno.
Working at Modal means joining one of the fastest-growing AI infrastructure organizations at an early stage, with many opportunities to grow within the company. Our team includes creators of popular open-source projects (e.g. Seaborn, Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
The Role:
Modal is seeking an experienced Forward Deployed Engineer (FDE) to partner with our sales team and drive technical sales success. As an FDE, you will be the technical voice in our sales process, working directly with Account Executives to help enterprise customers understand how Modal can transform their AI/ML infrastructure. You will:
Partner with Account Executives to identify, qualify, and close strategic enterprise opportunities
Lead technical discovery sessions with prospective customers to understand their current infrastructure, pain points, and requirements
Design and present compelling technical solutions that demonstrate how Modal addresses customer needs
Architect migration paths from existing cloud infrastructure (AWS, GCP, Azure) to Modal's serverless platform
Conduct technical demos, experiments, and proof-of-concepts that showcase Modal's capabilities
Navigate complex technical evaluations and address security, compliance, and integration concerns
Build trusted advisor relationships with technical decision-makers including CTOs, VPs of Engineering, and ML Engineering leads
Collaborate with product and engineering teams to communicate customer feedback and influence product roadmap
Support contract negotiations by providing technical expertise on implementation timelines, resource requirements, and success metrics
Requirements:
5+ years of experience in solutions engineering, sales engineering, or customer-facing technical roles
Deep hands-on experience with cloud platforms (AWS, GCP, Azure) including compute, storage, networking, and managed services
Strong knowledge of containerization technologies (Docker, Kubernetes, container orchestration)
Experience with databases (SQL/NoSQL), data pipelines, and distributed systems architecture
Understanding of ML/AI infrastructure challenges including model training, inference, and MLOps workflows
Familiarity with Infrastructure as Code (Terraform, Pulumi, CloudFormation) and CI/CD pipelines
Proven track record of supporting enterprise software sales cycles ($100K+ ACV)
Exceptional presentation and communication skills with ability to explain complex technical concepts to both technical and business audiences
Strong business acumen with understanding of enterprise buying processes and procurement
Experience building migration strategies and implementation roadmaps for large-scale infrastructure changes
Ability to work effectively with cross-functional teams including sales, product, and engineering
Experience selling or implementing serverless computing, container platforms, or ML infrastructure solutions preferred
Willingness to travel up to 30% for customer meetings and industry events
Based in or willing to relocate to New York, Stockholm, or San Francisco