Senior Platform Engineer – Infrastructure

Recruiting From Scratch•San Francisco, NY

2d•Remote

About The Position

We’re representing a venture-backed AI company building professional-grade AI systems for the insurance industry. The company develops technology that helps insurers automate and improve complex workflows across underwriting, claims, pricing, operations, and distribution. Its products are already deployed with leading insurers and are designed for environments where reliability, correctness, security, and trust are critical. Backed by investors including IA Ventures and Inspired Capital, the team includes talent from companies such as Facebook, Palantir, Google, Amazon, Uber, Mastercard, and McKinsey. The company operates as a globally distributed organization with a strong culture of ownership, experimentation, transparency, and high performance.

Requirements

5+ years of professional software engineering, platform engineering, infrastructure engineering, or DevOps experience.
Strong hands-on experience with cloud infrastructure and production systems.
Experience building or maintaining CI/CD pipelines.
Strong understanding of infrastructure reliability, security, performance, and scalability.
Experience with Infrastructure as Code, ideally Terraform.
Experience with Docker or comparable container technologies.
Experience with cloud and serverless technologies, including environments involving AWS Lambda and EC2.
Experience designing or operating asynchronous workflows.
Comfortable working with relational databases, ideally PostgreSQL.
Strong system design, debugging, and general software engineering fundamentals.
Strong coding ability; Python is the primary language, although engineers from other object-oriented programming backgrounds may be considered.
Able to independently own projects and drive them to completion with limited oversight.
Proactive communicator who surfaces blockers and keeps stakeholders informed.
Comfortable operating in a fast-moving environment where experimentation and iteration are expected.

Nice To Haves

Strong Python experience in production environments.
Experience building or operating distributed systems.
Experience with LLMs, generative AI, or infrastructure supporting AI/ML applications.
Experience optimizing cloud infrastructure for both performance and cost.
Experience designing observability and production incident-response practices.
Background supporting security- or compliance-sensitive enterprise software.
Experience working across application, data, ML, and infrastructure engineering teams.
Evidence of high ownership and the ability to solve ambiguous infrastructure problems independently.

Responsibilities

Build and improve the cloud infrastructure and internal tooling supporting a production AI platform.
Own and maintain CI/CD pipelines and improve the reliability and speed of engineering deployments.
Automate operational workflows and reduce manual infrastructure work.
Improve infrastructure performance, scalability, reliability, and security.
Monitor cloud usage and identify opportunities to improve infrastructure efficiency and cost.
Build and maintain infrastructure using Terraform and modern Infrastructure-as-Code practices.
Support containerized and serverless workloads across cloud environments.
Standardize development environments and deployment patterns across engineering teams.
Maintain and improve observability, monitoring, and incident response systems.
Partner with full-stack, data, ML, and DevOps engineers on scalable platform architecture.
Help maintain security and compliance requirements expected by enterprise insurance customers.
Debug complex production and infrastructure issues across distributed systems.
Take significant ownership over technical projects from design through production.