Senior Platform Engineer, NYC

Pinecone

Aug 3

Applications are closed

Job
Full-time
Junior (1-2 years)
New York

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience).
2+ years of experience in platform engineering, DevOps, or a similar role.
Strong proficiency in managing CI/CD pipelines and build automation tools (e.g., Jenkins, GitLab CI, CircleCI).
Hands-on experience with automated testing frameworks and tools.
Experience with cloud platforms (AWS, GCP, Azure) and cloud-native services.
Proficiency in infrastructure as code (IaC) tools such as Pulumi and Helm.
Solid scripting skills (e.g., Python, Bash) for automation and tooling.
Strong understanding of containerization (Docker) and orchestration (Kubernetes) technologies.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills, with the ability to work effectively in a fast-paced, dynamic environment.

Responsibilities

- We work closely with software engineers to align platform engineering efforts with development goals, ensuring seamless integration and support.
- We build and maintain tools such as CLIs and manage development environments to streamline workflows and enhance productivity.
- Communicating platform processes, configurations, and best practices ensures knowledge sharing through documentation and continuity, while providing support and guidance on building, testing, and deploying applications.
- We build our systems on top of Kubernetes and Cloud Run, with underlying infrastructure managed by Pulumi.
- Our deployment process utilizes Kubernetes tooling, including Helm, Helmfile, and ArgoCD, to ensure smooth and efficient operations.
- Using cloud-native technologies allows us to move fast while being present in different clouds.
- We manage a monorepo with multiple projects, requiring efficient build automation to ensure a quick feedback cycle by building only necessary artifacts.
- Our cross-platform environment necessitates building binaries for Intel and ARM architectures, utilizing containerization with technologies such as Docker builds, container registries, and image scanning.
- We focus on building robust Rust and Python applications to drive our core functionalities.
- We develop and maintain comprehensive automated testing frameworks, covering unit tests, integration tests, API tests, and property-based tests to ensure high-quality software releases.
- Automated tests are integrated into the CI/CD pipeline to catch issues early, while also ensuring that tests can be run quickly both locally and in CI environments.
- Testing distributed systems comes with unique challenges, and collaboration with engineering teams ensures comprehensive test coverage and effective solutions.
- We design, build, and maintain scalable, secure, and high-performance infrastructure across multiple cloud platforms (e.g., AWS, GCP, Azure), tackling the complexities of cross-cloud environments.
- Infrastructure as code (IaC) practices are implemented using tools like Pulumi, Helm, and Kubernetes to ensure consistency and efficiency.
- Monitoring infrastructure health, performance, and security is crucial, with proactive measures taken to address any issues and maintain robust operations.

FAQs

What is the main responsibility of a Senior Platform Engineer at Pinecone?

The main responsibility is the end-to-end management of platform infrastructure to improve the velocity of the engineering team, involving build processes, testing automation, developer tooling, deployment pipelines, and overall infrastructure reliability.

What kind of tools will I be working with in this role?

You will be working with tools like Kubernetes, Cloud Run, Pulumi, Helm, Helmfile, ArgoCD, and various CI/CD pipeline tools such as Jenkins, GitLab CI, or CircleCI.

What technologies does Pinecone use for application development?

Pinecone focuses on building robust applications using Rust and Python, along with employing containerization using Docker and orchestration with Kubernetes.

Is there a preference for experience with specific cloud platforms?

Yes, experience with cloud platforms such as AWS, GCP, and Azure is required.

What are the expected qualifications for applicants?

Applicants should hold a Bachelor’s degree in Computer Science, Engineering, or a related field, with 2+ years of experience in platform engineering or DevOps, proficiency in CI/CD pipeline management, automated testing frameworks, and scripting skills in languages like Python or Bash.

What kind of infrastructure management practices does Pinecone implement?

Pinecone implements Infrastructure as Code (IaC) practices using tools like Pulumi, Helm, and Kubernetes to ensure consistency and efficiency in managing infrastructure.

What kind of benefits does Pinecone offer to its employees?

Pinecone offers comprehensive health coverage, free mental health therapy sessions, equity awards, 401(k), flexible time off, paid parental leave, and a WFH equipment stipend, among other benefits.

What should I do if I don’t meet all the qualifications listed for the job?

Pinecone encourages all interested candidates to apply, even if they don’t meet every qualification, as the priority is finding the best candidate for the position.

What is the compensation range for this position?

The compensation range for the Senior Platform Engineer position is $158K - $190K.

How does Pinecone promote diversity and inclusion in its hiring practices?

Pinecone prioritizes diversity, equity, inclusion, and belonging (DEIB) in its hiring practices, ensuring that all qualified applicants receive consideration for employment without regard to various legally protected statuses.

Pinecone

The Pinecone vector database: Long-term memory for AI.

Technology

Industry

51-200

Employees

2019

Founded Year

Mission & Purpose

Pinecone is a fully managed vector database that makes it easy to add vector search to production applications. It combines state-of-the-art vector search libraries, advanced features such as filtering, and distributed infrastructure to provide high performance and reliability at any scale. No more hassles of benchmarking and tuning algorithms or building and maintaining infrastructure for vector search. We are engineers who built large machine learning platforms, databases, and search engines at AWS, Yahoo, Splunk, Databricks, and more. We are scientists who transformed businesses with ML applications such as shopping recommendations, online advertising, semantic search, anomaly detection, and more. We are researchers who collectively published more than 100 academic papers and patents on machine learning, systems, and algorithms.