Software Engineer, Platform
Build and evolve shared platform infrastructure, data systems, and developer tooling for AI products. The role requires 5+ years of backend engineering experience, distributed systems expertise, and familiarity with cloud, orchestration, databases, and CI/CD technologies.
About the job
Responsibilities
- Design and implement foundational platforms and systems.
- Collaborate with cross-functional teams to define requirements, design solutions, and deliver features.
- Experiment with emerging AI techniques and technologies.
- Improve programming practices, processes, and development tools.
- Present technical information and provide guidance on development processes and technologies.
Requirements
- 5+ years of full-time engineering experience after graduation, specializing in back-end systems.
- Experience developing highly scalable and reliable distributed systems on public cloud platforms.
- Experience building document retrieval and understanding systems, including RAG.
- Demonstrated ownership and delivery of successful engineering projects.
- Strong communication and collaboration skills, including explaining complex technical concepts to non-technical stakeholders.
- Experience with containerization and deployment technologies such as Kubernetes, Terraform, and Docker.
- Experience with long-running agent and code orchestration platforms such as Temporal.
- Expertise with structured databases, including Postgres.
- Strong knowledge of software engineering best practices and CI/CD tooling, including CircleCI and GitHub Actions.
Nice-to-haves
- Experience with multiple cloud platforms, including GCP, AWS, Azure, Oracle, or on-premises environments.
- Experience persisting contextual data with knowledge graphs and hierarchical indexes.
- Experience with large-scale data solutions such as Databricks and Snowflake.
- Experience with authentication and authorization systems such as Zanzibar and Authz.
- Experience scaling technical products at hyper-growth startups.
Skills
Backend Systems, Distributed Systems, Public Cloud, RAG, Kubernetes, Terraform, Docker, Temporal, Postgres, CI/CD, CircleCI, GitHub Actions, AWS, Azure, Databricks
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