Solutions Architect

Modal is hiring a Solutions Architect in San Francisco, United States. It pays $200k-$280k a year and Level rates it ; you can apply on Modal.

Level's read on this job

Works on AI ●●●○ is how Level rates this solutions architect role: the daily work is on AI products, without building the model.
Pay on this posting starts 19% higher than the typical solutions architect posting on Level.
The posting mentions MLOps among its tools and skills.
Modal has 42 other open roles on Level.

AI in this role

ml-ops

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 Ramp, 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.

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 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%

How we rate this

Solutions Architect at Modal rates 74 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Solutions Architect is an open job at Modal.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $200k-$280k a year.
The role is based in San Francisco.
The job was posted on February 20, 2026.
Applications are handled by Modal. Apply on Modal

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML Ops

Also common in solutions architect jobs at this level

Generative AI LLM Machine learning SQL RAG AI agents

Pay

This job starts at: $200k
Typical solutions architect job: $168k

This posting starts 19% above the typical solutions architect job. See solutions architect jobs

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: ML Ops. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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