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About the Role

As a Software Engineer on our Cloud team, you'll play a key role in building and scaling the technology powering our autonomous scientific discovery platform. You'll have significant ownership over the architecture and operations of our cloud deployment product, working alongside a small team of experienced engineers who care deeply about building world class software. Our mission is to build an AI scientist, and you'll be part of the team which enables Edison to scale to the largest research organizations in the world.

Responsibilities

Design, build, and operate systems for platform deployment within client cloud infrastructure (AWS/GCP).
Develop operators, infrastructure tooling, and automation for the bring your own cloud (BYOC) deployment process.
Support client deployments and onboarding, working directly with enterprise clients' engineering and security teams.
Partner with the forward deployed engineering team to scope requirements and deliver on engagements.
Diagnose and solve bottlenecks in the BYOC process to streamline operations and expand capacity.
Contribute to technical decision making and architecture for the BYOC product.
Harden security, reliability, and observability of deployments in customer-controlled environments.

Requirements

4+ years of experience building and operating backend or infrastructure systems in production.
Proficiency in Python for backend development and infrastructure tooling.
Deep familiarity with cloud products (AWS/GCP), security, and deployment operations.
Strong understanding of application network architecture including VPCs, DNS, secrets, proxies, etc.
Hands-on experience with infrastructure-as-code tools (Terraform, Pulumi, or Crossplane) and GitOps workflows.
Strong communication skills and comfort working directly with enterprise clients.
Experience with Kubernetes, multi-tenant architectures, or deploying software into customer-controlled environments.
Experience with AI applications or scientific computing solutions.
Prior experience in startups or small teams with significant architectural ownership and ambiguity.
Experience scaling systems or platforms through periods of rapid growth.

Skills

Python
AWS
GCP
Cloud Security
Deployment Operations
VPCs
DNS
Secrets Management
Proxies
Terraform
Pulumi
Crossplane
GitOps
Kubernetes
Multi-tenant Architectures
AI Applications
Scientific Computing

Location

San Francisco

Work Type

On-site
Full-time

Experience Level

4+ years of experience

Salary/Compensations

Competitive salary and equity

Benefits

Full healthcare coverage (100% premium for employee and dependents)
Yearly new parent stipend
Fertility coverage through Carrot
Mental health support through Rula
12 weeks of paid parental leave
Yearly employer-funded pet care stipend
Commuter benefits (pre-tax transit and parking)
401(k) company matching
$300 quarterly health and wellness benefit
Daily catered lunch
Dinner provided when working late
Regular team off-sites and company events

About the Company

Edison Scientific builds and deploys AI scientist agents to accelerate science and the development of new medicines.
Ambitious team run by scientists and engineers from leading institutions across biology, physics, chemistry, and AI.

Equal Opportunity

Edison Scientific is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.