Infrastructure Engineer – San Francisco

Syndesus; San Francisco (CA); On-site; USD 150,000 - 300,000; Full time

Benefits offered by this job

Equity

On-site (SF/NYC)

Job summary

Syndesus is seeking an Infrastructure Engineer to help build the foundational cloud and data platforms for an ambitious AI startup. You will join as one of the first 20 engineers, owning critical infra from design to production and scale.

This is a hands-on, high-impact role in a fast-growing environment. You will work across AWS, GCP, and Azure, leverage Kubernetes and IaC tools, and collaborate with AI research and product teams to enable scalable, secure, and reliable infrastructure for

Qualifications

• 4–5+ years of cloud, platform, infrastructure, DevOps, SRE, or data infrastructure experience.
• Strong expertise with AWS, GCP, or Azure.
• Strong production experience with Kubernetes and Docker/containerization.
• Experience with Terraform, Pulumi, or other IaC tooling.
• Experience building CI/CD pipelines and production deployment infrastructure.
• Experience with data ingestion, ETL, or data pipelines, using Spark, Kafka, or Databricks.
• Experience with monitoring and observability tools such as Datadog, Prometheus, Grafana.
• 0-to-1 infrastructure ownership; building systems from scratch.
• Experience in a high-growth startup or similar engineering environment.
• Strong Computer Science academic background.

Responsibilities

• Design and build scalable cloud infrastructure across AWS, GCP, and Azure.
• Build and operate Kubernetes and containerized production environments.
• Develop infrastructure for secure private cloud and BYOC deployments.
• Build complex data ingestion and ETL pipelines for structured and unstructured financial data.
• Implement infrastructure-as-code using Terraform, Pulumi, or similar tooling.
• Build and improve CI/CD, monitoring, logging, alerting, and observability systems.
• Design security-first infrastructure with access controls, audit trails, tenant isolation, and data governance.
• Partner with AI Research and Product teams on LLM inference, training, GPU workloads, and agent infrastructure.
• Own infrastructure projects from initial architecture through production and scale.
• Collaborate with cross-functional teams to align infra with product goals.

Skills

Cloud engineering

AWS/GCP/Azure

Kubernetes

Docker

IaC (Terraform/Pulumi)

CI/CD

Data pipelines

Datadog/Prometheus/Grafana

0-to-1 ownership

Startup experience

CS background

Education

Bachelor's in Computer Science

Tools

Kubernetes

Docker

Terraform

Pulumi

Datadog

Spark

Kafka

Databricks

Job description

Infrastructure Engineer (San Francisco / New York City, On-Site)

Tech Stack:

AWS, GCP, Azure, Kubernetes, Docker, Terraform, Pulumi, Datadog, Spark, Kafka, Databricks, CI/CD, AI/ML Infrastructure, LLM Infrastructure

$150,000–$300,000 USD + Equity

Why This Role

This is not a traditional DevOps role.

This is not maintaining mature infrastructure.

This is an opportunity to build the infrastructure foundation of a $50M Series A AI startup as one of its first 20 engineers.

Backed by one of Silicon Valley’s leading venture firms, the company is building an enterprise AI data platform for financial services. The founders previously helped scale category-defining technology companies from fewer than 50 employees through hypergrowth.

Customer demand is already exceeding engineering capacity—the company is actively turning down business because it needs more engineers to support growth.

You’ll have early-stage ownership with the funding, customer traction, and experienced leadership to build at serious scale.

What You’ll Do

• Design and build scalable cloud infrastructure across AWS, GCP, and Azure.
• Build and operate Kubernetes and containerized production environments.
• Develop infrastructure for secure private cloud and BYOC deployments.
• Build complex data ingestion and ETL pipelines for structured and unstructured financial data.
• Implement infrastructure-as-code using Terraform, Pulumi, or similar tooling.
• Build and improve CI/CD, monitoring, logging, alerting, and observability systems.
• Design security-first infrastructure with access controls, audit trails, tenant isolation, and data governance.
• Partner with AI Research and Product teams on LLM inference, training, GPU workloads, and agent infrastructure.
• Own infrastructure projects from initial architecture through production and scale.

Skills

• 4–5+ years of cloud, platform, infrastructure, DevOps, SRE, or data infrastructure engineering experience.
• Strong expertise with AWS, GCP, or Azure.
• Strong production experience with Kubernetes and Docker/containerization.
• Experience with Terraform, Pulumi, or other infrastructure-as-code (IaC) tooling.
• Experience building CI/CD pipelines and production deployment infrastructure.
• Experience with data ingestion, ETL, or data pipelines , ideally using technologies such as Spark, Kafka, or Databricks.
• Experience with monitoring and observability tools such as Datadog, Prometheus, or Grafana.
• Demonstrated 0-to-1 infrastructure ownership and experience building systems from scratch.
• Experience in a high-growth startup or another sophisticated, high-performing engineering environment.
• Graduated with a strong Computer Science academic background.

Nice to Have

• AI/ML infrastructure, LLM inference/training, GPU infrastructure, or agent infrastructure.
• Multi‑cloud infrastructure across AWS, GCP, and Azure.
• SageMaker, Bedrock, or other cloud-native AI/ML platforms.
• Private cloud, BYOC, or enterprise deployment experience.
• Financial services or another regulated industry.
• Experience with SOC, SOX, GDPR, security, compliance, or data governance.

Why Join

• $50M Series A backed by a top-tier Silicon Valley investor.
• Join as one of the first 20 engineers and shape the infrastructure architecture from the ground up.
• Experienced founders who have previously helped scale category-defining technology companies through hypergrowth.
• Exceptional customer pull with more inbound demand than the current engineering team can support.
• Infrastructure is the product — cloud, data, security, and AI infrastructure are central to what customers are buying.
• Hard AI + infrastructure problems involving sensitive financial data, LLM workloads, multi-cloud deployments, and enterprise-grade security.
• High ownership, high-trust culture with flexible hours and a strong engineering bar.

Compensation

• $150,000–$300,000 USD base salary
• Competitive equity
• San Francisco or New York City
• On-site with flexible working hours