Infrastructure / Platform Engineer

Location

San Francisco, CA

On-site role requiring five to six days per week in the San Francisco office.

Compensation

$175,000 – $275,000 Base + 0.4–0.8% Equity

Visa

Open to visa transfers, including H-1B transfers, TN, and O-1. New H-1B sponsorship is not available.

Company Stage

Early-Stage / Venture-Backed AI Infrastructure Company

Industry

Artificial Intelligence, Infrastructure, Platform Engineering, Developer Tools, Enterprise Software, B2B SaaS, Workflow Automation, AI Agents, Cloud Infrastructure, Integration Platforms

About the Company

Our client is building an AI-native integration platform that automates mission-critical integrations for companies operating in the physical economy.

The platform uses specialized AI agents to handle the full lifecycle of integrations, from understanding requirements through writing, testing, and deploying integration code into production.

The company is solving a fundamental connectivity problem where businesses still rely heavily on custom integrations that are expensive, time-consuming, and difficult to maintain.

The team is exceptionally small and highly technical, with infrastructure currently owned by the CTO. The company has paying enterprise customers with production integrations and significant demand, creating an immediate need for a dedicated infrastructure and platform engineer.

As the first Infrastructure / Platform Engineer, you'll own the entire infrastructure layer from the ground up, working directly with the CTO to build the runtime, agent infrastructure, observability systems, and self-hostable deployment architecture that powers mission-critical enterprise integrations.

This is a highly autonomous individual contributor role where you'll establish the technical patterns that future infrastructure engineers will build on, while eventually helping recruit and grow the infrastructure team.

What You'll Do

• Own the infrastructure and platform layer end-to-end
• Build the core runtime infrastructure powering mission-critical integrations
• Design and build a scalable integration runtime similar to a "Vercel for integrations"
• Build durable execution systems for long-running integration workflows
• Design sandboxed execution environments for safely running integration code
• Build self-healing infrastructure that can detect and recover from failures
• Build and scale the agent infrastructure powering coding agents
• Support AI agents that write, test, and deploy integration code into production
• Design reliable execution environments for autonomous software agents
• Build infrastructure that allows agents to operate safely and reliably in production
• Design and implement the observability layer for integrations and AI agents
• Build monitoring, logging, tracing, and alerting systems
• Give enterprise customers visibility into the health and behavior of their integrations
• Architect and ship single-tenant deployments for enterprise customers
• Build self-hostable versions of the platform that customers can run inside their own cloud environments
• Design multi-cloud deployment architectures across AWS, Azure, GCP, and similar environments
• Build reusable infrastructure and platform components that can support future deployments
• Operate and scale production Kubernetes clusters
• Debug complex Kubernetes and cloud infrastructure issues
• Design reliable cloud infrastructure for high-growth production workloads
• Build deployment systems that support rapid and repeatable customer environments
• Establish infrastructure patterns, standards, and best practices for the engineering organization
• Work closely with the CTO on infrastructure architecture and technical strategy
• Make independent architectural decisions in a highly ambiguous environment
• Identify infrastructure bottlenecks and improve system reliability and performance
• Build infrastructure from scratch rather than simply maintaining existing systems
• Balance speed of execution with reliability, security, scalability, and operational simplicity
• Help identify opportunities to generalize customer-specific infrastructure requirements into reusable platform capabilities
• Contribute to the architecture of the company's long-term infrastructure platform
• Help recruit strong infrastructure engineers as the team grows
• Eventually help build and lead the infrastructure engineering organization
• Take ownership of infrastructure outcomes rather than simply completing assigned tickets
• Ship continuously in a fast-moving startup environment
• Operate with high autonomy and minimal hand-holding
• Establish the technical foundation that future infrastructure engineers will build upon

Ideal Candidate Background

Experience Requirements

• 3–12 years of experience in cloud infrastructure, platform engineering, or closely related engineering roles
• Strong experience owning core infrastructure end-to-end
• Experience at a venture-backed startup or high-growth technology company preferred
• Experience building infrastructure from scratch
• Experience working on greenfield infrastructure or platform projects
• Strong production infrastructure engineering experience
• Experience operating infrastructure in fast-moving environments
• Experience owning systems through architecture, implementation, deployment, and ongoing operation
• Experience working closely with engineering leadership or technical founders
• Experience operating independently with significant technical ownership
• Experience working in ambiguous and rapidly changing environments
• Experience building infrastructure for production software systems
• Experience working with cloud platforms at meaningful scale
• Experience with Kubernetes in production environments
• Experience building and shipping platform code rather than purely operating infrastructure
• Experience working on complex distributed systems preferred
• Experience working at high-growth startups or strong technology scale-ups preferred
• Experience with multi-cloud or self-hostable infrastructure preferred
• Strong individual contributor mentality
• Demonstrated ability to solve difficult infrastructure problems independently
• Track record of building reliable systems from the ground up

Technical Requirements

• Deep production Kubernetes expertise
• Experience operating, scaling, and debugging Kubernetes clusters
• Strong expertise in AWS, Azure, or GCP
• Strong understanding of cloud infrastructure architecture
• Experience designing production-grade infrastructure
• Experience with containerization and orchestration
• Strong understanding of networking, compute, storage, and cloud primitives
• Experience designing scalable deployment architectures
• Experience building platform infrastructure rather than solely performing SRE or DevOps functions
• Experience writing production platform or infrastructure code
• Strong understanding of distributed systems
• Experience with infrastructure automation and deployment systems
• Experience designing reliable runtime environments
• Experience with observability systems including logging, metrics, tracing, and monitoring
• Experience building systems for production reliability and fault tolerance
• Experience designing secure and isolated execution environments preferred
• Experience with sandboxing or workload isolation preferred
• Experience building self-hostable or single-tenant deployments preferred
• Experience designing multi-cloud infrastructure preferred
• Experience working with AWS, Azure, or GCP deployment environments
• Experience with infrastructure-as-code and automated deployment workflows preferred
• Experience building systems that support AI or agentic workloads preferred
• Familiarity with AI agent infrastructure and autonomous software systems preferred
• Experience supporting production workloads with complex operational requirements
• Strong debugging and incident-response capabilities
• Strong understanding of reliability, scalability, and performance
• Ability to quickly understand unfamiliar infrastructure systems
• Ability to make pragmatic infrastructure trade-offs in an early-stage environment
• Comfortable building infrastructure with limited existing patterns or documentation

Education

• Bachelor's degree preferred
• Computer Science, Engineering, Mathematics, or equivalent technical disciplines preferred
• Degree from a top-30 Computer Science program preferred when professional experience is not sufficiently strong
• Strong practical infrastructure engineering experience can compensate for academic pedigree

Soft Skills

• Extremely high agency and ownership
• Strong bias toward action
• Comfortable operating independently
• Strong builder mentality
• Comfortable building infrastructure from scratch
• Strong technical judgment
• Comfortable making architectural decisions with incomplete information
• Comfortable operating in highly ambiguous environments
• Strong problem-solving ability
• Excellent debugging instincts
• Strong sense of urgency
• Comfortable shipping continuously
• Comfortable working directly with technical founders
• Low-ego and highly collaborative
• Strong communication skills
• Able to explain complex infrastructure concepts clearly
• Comfortable taking full responsibility for infrastructure outcomes
• Strong product and business judgment
• Comfortable balancing reliability with speed
• Comfortable working without extensive processes or structure
• Strong ownership of production systems
• Comfortable operating as a true individual contributor
• Willing to help recruit future infrastructure engineers
• Interested in eventually helping build an infrastructure team
• Comfortable working in a very small engineering organization
• Excited by greenfield infrastructure challenges
• Comfortable with high-growth startup intensity
• Strong attention to operational reliability
• Comfortable dealing with difficult production problems
• Comfortable working onsite five to six days per week in San Francisco

Compensation & Benefits

• Base Salary: $175,000 – $275,000
• Competitive equity package of approximately 0.4–0.8%
• Opportunity to become the first dedicated infrastructure hire
• Ownership of the entire infrastructure and platform layer
• Opportunity to build a cloud platform from scratch
• Opportunity to design infrastructure patterns used by future engineers
• Exposure to AI agents and autonomous software systems
• Opportunity to build infrastructure for production AI workloads
• High degree of technical ownership and autonomy
• Direct partnership with the CTO
• Opportunity to work on multi-cloud and self-hostable deployments
• Opportunity to build enterprise-grade observability and deployment systems
• Significant influence over the company's technical architecture
• Opportunity to help recruit and grow the infrastructure team
• Potential path toward infrastructure technical leadership
• Fast-paced startup environment with significant technical growth
• Five-to-six-day in-office environment in San Francisco
• H-1B transfers, TN, and O-1 visa options available

Why Join

This is an opportunity to become the first dedicated infrastructure and platform engineer at a highly technical AI startup and own the foundational infrastructure powering an agentic integration platform.

You'll work directly with the CTO to build the infrastructure layer from the ground up, including the integration runtime, agent execution environment, observability platform, deployment systems, and self-hostable enterprise architecture.

Rather than inheriting an established infrastructure organization, you'll define the patterns, architecture, and engineering standards that future infrastructure engineers will build on.

The role offers unusually broad technical ownership. You'll work across Kubernetes, cloud infrastructure, distributed systems, deployment architecture, observability, AI agents, and enterprise infrastructure while solving problems that directly impact production customers.

You'll also have the opportunity to shape the infrastructure organization itself by helping recruit future engineers and potentially growing into a technical leadership role as the company scales.

If you enjoy greenfield infrastructure, Kubernetes, cloud architecture, AI agents, distributed systems, high ownership, and building foundational systems from scratch, this role offers exceptional scope and technical impact.