Staff Platform Infrastructure Engineer

Together AI is hiring a Staff Platform Infrastructure Engineer in San Francisco, United States. It pays $240k-$280k a year and Level rates it ; you can apply on Level.

AI in this role

cursorelevenlabsdecagon

fine-tuning

About the Role

Together AI is hiring a Staff Platform Infrastructure Engineer to drive the service and platform infrastructure strategy across our engineering organization. This is a hands-on technical leadership role with the opportunity to establish a new team and shape its direction, defining the golden path for how services are built and operated at Together.

This role will support mission-critical Product and Platform teams by providing a stable, scalable service infrastructure foundation for building and operating customer-facing and internal services. The focus is on making that foundation reliable, repeatable, and easy for teams to adopt.

You'll own and evolve crucial shared infrastructure, roll out new infrastructure patterns and platform capabilities to service teams, and coordinate with other infrastructure teams to ensure services are built on company-wide foundations.

In your first year, you might:

Ship a new golden-path service template (scaffolding, Helm chart, CI/CD, and GitOps) and move the first set of services onto it.
Implement zero-trust policies on our production clusters.
Collaborate with DevProd and SREs on the migration to Kargo.
Hire and grow the initial Platform Infrastructure team.

Responsibilities

Set the technical direction for service infrastructure across Kubernetes, AWS, CDN and edge networking, and related operational patterns.
Design and build reusable infrastructure primitives, such as Helm charts and Terraform modules.
Build self-service platform capabilities, operational runbooks, and AI-assisted tooling that accelerate service development and operations.
Partner closely with service teams to modernize existing services and adopt stronger infrastructure patterns.
Work with Infrastructure, Networking, and Security teams to translate company-wide platform standards into practical service-level implementations.
Lead cross-company infrastructure initiatives such as Terraform CI/CD, Kubernetes networking, zero-trust service communication, policy-as-code, and cross-DC and cross-provider networking.

Requirements

7+ years of professional experience in platform engineering, service infrastructure, SRE, cloud infrastructure, or a related field.
Deep production experience with Kubernetes and AWS, including operating shared infrastructure for deployment, networking, identity, scaling, or service reliability. Examples include EKS, IAM, VPC, Route 53, CloudFront, and ECR.
Strong experience with Terraform and infrastructure delivery automation.
Working knowledge of service and edge networking, including DNS, TLS, CDNs, load balancing, and ingress and egress.
Proficiency in Go, Python, TypeScript, or another systems or infrastructure-oriented programming language.
Experience building reusable infrastructure used by multiple engineering teams and helping those teams adopt it in production.
Proven ability to lead ambiguous, cross-functional infrastructure initiatives, with strong written technical communication and a track record of driving adoption across teams you don't manage.

Preferred Qualifications

Experience with GitHub Actions, GitOps workflows, and service scaffolding.
Experience with Argo CD, Argo Rollouts, or Kargo.
Experience designing or operating CDNs, WAFs, edge infrastructure, or Layer 4 networking
Experience with service meshes, zero-trust networking, policy-as-code, multi-region or hybrid infrastructure, or supply-chain security.
Experience operating distributed streaming systems (Kafka, Flink, Spark Streaming) as shared platform services for data teams.
Experience building or applying AI-assisted tooling to improve service development or operations.

About Together AI

Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $240,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy

How we rate this

Staff Platform Infrastructure Engineer at Together AI rates 63 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. Open the description and count.

Key facts

Staff Platform Infrastructure Engineer is an open job at Together AI.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $240k-$280k a year.
The role is based in San Francisco.
The job was posted on July 10, 2026.
Seniority: lead.
Applications are handled by Together AI. Apply on Together AI

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Fine-tuningCursorElevenlabsDecagon

Questions you could be asked

Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Walk me through how you've used Cursor in your day-to-day work.
What are the limits of Elevenlabs that you've run into, and how did you work around them?
What's a project where you used Decagon hands-on?
Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

List these exact terms on your resume: Fine-tuning, Cursor, Elevenlabs, and Decagon. 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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