Job Summary
Forward Deployed Engineer
Platform Team
About the product
We build an AI-powered application security platform. It reads source code, finds security vulnerabilities, and then produces a fix that a person reviews and approves. Customers install it and run it inside their own cloud environment. The stack is Python (Langgraph, FastAPI, Pydantic V2), TypeScript, React, PostgreSQL, Kubernetes and the major cloud platforms.
About the role
You'll take the platform into customer environments, deploy it, get it working against real codebases, and fix what breaks.
It's an engineering role that faces customers. You'll read and debug the code yourself instead of escalating. Much of the value you create ends up written down: reproducible issues for the engineering team, and documentation that makes the next deployment easier than the last.
What you'll do
- Run customer deployments end to end, from installation through to a working outcome.
- Be the first real user of every deployment and find the problems before customers do.
- Turn field failures into precise, reproducible engineering issues.
- Write installation runbooks, troubleshooting guides and enablement material.
- Tell customer-specific needs apart from general requirements, and route each one properly.
What we're looking for
- Hands-on engineering ability. You can read unfamiliar source code and debug it.
- Confidence working directly with customers, including when something has gone wrong.
- Enough Kubernetes and CI/CD to work independently in someone else's environment.
- Strong documentation habits.
- Comfort with ambiguity, and with infrastructure you didn't design.
- The stack is Python (Langgraph, FastAPI, Pydantic V2), TypeScript, React, PostgreSQL, Kubernetes and the major cloud platforms.
Nice to have
- Breadth across build ecosystems and languages. Breadth is worth more than depth here.
- Solutions engineering or technical consulting, with a product mindset.
- Taking a proof of concept through to a signed agreement.
Key Responsibilities
Forward Deployed Engineer
Platform Team
About the product
We build an AI-powered application security platform. It reads source code, finds security vulnerabilities, and then produces a fix that a person reviews and approves. Customers install it and run it inside their own cloud environment. The stack is Python (Langgraph, FastAPI, Pydantic V2), TypeScript, React, PostgreSQL, Kubernetes and the major cloud platforms.
About the role
You'll take the platform into customer environments, deploy it, get it working against real codebases, and fix what breaks.
It's an engineering role that faces customers. You'll read and debug the code yourself instead of escalating. Much of the value you create ends up written down: reproducible issues for the engineering team, and documentation that makes the next deployment easier than the last.
What you'll do
- Run customer deployments end to end, from installation through to a working outcome.
- Be the first real user of every deployment and find the problems before customers do.
- Turn field failures into precise, reproducible engineering issues.
- Write installation runbooks, troubleshooting guides and enablement material.
- Tell customer-specific needs apart from general requirements, and route each one properly.
What we're looking for
- Hands-on engineering ability. You can read unfamiliar source code and debug it.
- Confidence working directly with customers, including when something has gone wrong.
- Enough Kubernetes and CI/CD to work independently in someone else's environment.
- Strong documentation habits.
- Comfort with ambiguity, and with infrastructure you didn't design.
- The stack is Python (Langgraph, FastAPI, Pydantic V2), TypeScript, React, PostgreSQL, Kubernetes and the major cloud platforms.
Nice to have
- Breadth across build ecosystems and languages. Breadth is worth more than depth here.
- Solutions engineering or technical consulting, with a product mindset.
- Taking a proof of concept through to a signed agreement.
Skill Requirements
Forward Deployed Engineer
Platform Team
About the product
We build an AI-powered application security platform. It reads source code, finds security vulnerabilities, and then produces a fix that a person reviews and approves. Customers install it and run it inside their own cloud environment. The stack is Python (Langgraph, FastAPI, Pydantic V2), TypeScript, React, PostgreSQL, Kubernetes and the major cloud platforms.
About the role
You'll take the platform into customer environments, deploy it, get it working against real codebases, and fix what breaks.
It's an engineering role that faces customers. You'll read and debug the code yourself instead of escalating. Much of the value you create ends up written down: reproducible issues for the engineering team, and documentation that makes the next deployment easier than the last.
What you'll do
- Run customer deployments end to end, from installation through to a working outcome.
- Be the first real user of every deployment and find the problems before customers do.
- Turn field failures into precise, reproducible engineering issues.
- Write installation runbooks, troubleshooting guides and enablement material.
- Tell customer-specific needs apart from general requirements, and route each one properly.
What we're looking for
- Hands-on engineering ability. You can read unfamiliar source code and debug it.
- Confidence working directly with customers, including when something has gone wrong.
- Enough Kubernetes and CI/CD to work independently in someone else's environment.
- Strong documentation habits.
- Comfort with ambiguity, and with infrastructure you didn't design.
- The stack is Python (Langgraph, FastAPI, Pydantic V2), TypeScript, React, PostgreSQL, Kubernetes and the major cloud platforms.
Nice to have
- Breadth across build ecosystems and languages. Breadth is worth more than depth here.
- Solutions engineering or technical consulting, with a product mindset.
- Taking a proof of concept through to a signed agreement.
Other Requirements
Forward Deployed Engineer
Platform Team
About the product
We build an AI-powered application security platform. It reads source code, finds security vulnerabilities, and then produces a fix that a person reviews and approves. Customers install it and run it inside their own cloud environment. The stack is Python (Langgraph, FastAPI, Pydantic V2), TypeScript, React, PostgreSQL, Kubernetes and the major cloud platforms.
About the role
You'll take the platform into customer environments, deploy it, get it working against real codebases, and fix what breaks.
It's an engineering role that faces customers. You'll read and debug the code yourself instead of escalating. Much of the value you create ends up written down: reproducible issues for the engineering team, and documentation that makes the next deployment easier than the last.
What you'll do
- Run customer deployments end to end, from installation through to a working outcome.
- Be the first real user of every deployment and find the problems before customers do.
- Turn field failures into precise, reproducible engineering issues.
- Write installation runbooks, troubleshooting guides and enablement material.
- Tell customer-specific needs apart from general requirements, and route each one properly.
What we're looking for
- Hands-on engineering ability. You can read unfamiliar source code and debug it.
- Confidence working directly with customers, including when something has gone wrong.
- Enough Kubernetes and CI/CD to work independently in someone else's environment.
- Strong documentation habits.
- Comfort with ambiguity, and with infrastructure you didn't design.
- The stack is Python (Langgraph, FastAPI, Pydantic V2), TypeScript, React, PostgreSQL, Kubernetes and the major cloud platforms.
Nice to have
- Breadth across build ecosystems and languages. Breadth is worth more than depth here.
- Solutions engineering or technical consulting, with a product mindset.
- Taking a proof of concept through to a signed agreement.