Solutions Architect
$250k+Application analysis
Solutions Architect at Modal is a forward deployed enterprise software role for engineers who want customer-facing technical work with real deployment ownership.
Reading this role
This Solutions / Sales Engineering role centers on technical discovery, demos, POCs, and helping buyers build internal consensus. Key signals from the listing: Kubernetes / containers, Terraform / IaC, AWS, Azure.
About Modal
Enterprise software forward deployed engineers drive adoption, integration, and measurable customer outcomes. The role is anchored in San Francisco, so expect on-site customer work in that region.
Signals in the listing
Stand out for Solutions Architect
- Lead your application with one paragraph tying Solutions Architect to a specific customer or deployment you owned — Modal hires for shipped outcomes, not tool lists.
- Bring a tight demo narrative: customer pain, live workflow, and measurable before/after — treat the interview like a compressed POC.
- Show how you qualify opportunities and say no to bad-fit pilots; Modal values technical judgment in customer-facing roles.
- For Kubernetes-heavy roles, describe a cluster you operated: upgrades, networking, secrets, observability, and how you debugged a production outage.
- Link to or describe Terraform modules you wrote with environment promotion strategy (dev → staging → prod) and how you handled state and drift.
- This role is tied to San Francisco — mention willingness to work on-site with customers and any existing ties to that market (clients, partners, or domain knowledge).
Stand out at Modal
- Demonstrate stakeholder management with a concrete example — Modal will probe for specifics, not buzzwords.
- Demonstrate integration skill with a concrete example — Modal will probe for specifics, not buzzwords.
- Prepare stories that move from discovery → pilot → production with named outcomes.
- Read recent engineering blog posts, product launches, and customer stories on modal.com — reference one explicitly in your outreach to show genuine interest.
Tailored from this listing’s title, company, and description. Always verify requirements on the company careers page before applying.
Role description
About Us:
AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable https://modal.com/blog/lovable-case-study, Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C https://modal.com/blog/modal-series-c at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
The Role:
Modal is hiring a high-impact Solutions Architect to drive technical strategy across our most strategic enterprise accounts. You will operate as the executive technical counterpart to Enterprise Account Executives, leading complex evaluations, shaping infrastructure modernization roadmaps, and driving multi-product adoption across AI/ML workloads. This role is not demo support. It is a strategic, consultative position requiring strong architectural depth, executive presence, and the ability to influence 7–8 figure infrastructure decisions. You will work directly with CTOs, VPs of Engineering, and ML platform leaders to help them rethink how AI infrastructure should be built and operated. If you thrive in high-velocity technical sales environments and want to shape the infrastructure layer powering modern AI companies, this role is for you.
What You’ll Do:
- Own the technical strategy for large, complex enterprise accounts
- Partner with Enterprise Account Executives to drive 6–7+ figure opportunities from qualification through close
- Lead deep technical discovery across platform, ML, DevOps, and infrastructure stakeholders
- Architect end-to-end migration strategies from AWS, GCP, or Azure to Modal’s serverless infrastructure
- Drive executive-level technical conversations that connect infrastructure architecture to business impact (velocity, cost efficiency, reliability)
- Design and oversee proof-of-concepts that demonstrate production-grade scalability and performance
- Navigate security reviews, compliance discussions, and procurement processes with confidence
- Build durable relationships with technical champions and executive sponsors
- Orchestrate cross-functional virtual account teams (Sales, Product, Engineering, Support) to ensure successful adoption
- Influence Modal’s product roadmap by surfacing structured enterprise feedback
- Mentor other Solutions Architects and contribute to technical best practices across the team
Requirements:
- 5+ years in Solutions Engineering, Sales Engineering, or enterprise-facing technical roles in infrastructure, cloud, or developer platforms
- Demonstrated success driving complex enterprise sales cycles ($250K+ ACV; experience with $1M+ ARR accounts strongly preferred)
- Experience working with large, sophisticated Bay Area technology companies or global enterprises
- Deep expertise in cloud infrastructure (AWS, GCP, Azure) including compute, networking, storage, and managed services
- Strong architectural understanding of containers and orchestration (Docker, Kubernetes)
- Experience designing distributed systems and production data platforms
- Strong working knowledge of ML/AI infrastructure (training pipelines, inference systems, GPU workloads, MLOps)
- Experience leading cloud migration or infrastructure modernization initiatives
- Familiarity with Infrastructure as Code (Terraform, Pulumi, CloudFormation) and CI/CD systems
- Production programming experience in Python strongly preferred
- Executive-level communication skills with the ability to influence technical and business stakeholders
- Proven ability to lead cross-functional virtual teams in high-stakes account environments
- Strong business acumen and understanding of enterprise procurement and buying processes
- Willingness to travel up to 30%