Engineering Leader

Collinear AI•Sunnyvale, CA

About The Position

As the Engineering Leader, you will own the architecture, reliability, and evolution of Collinear’s AI agent improvement product offerings. This role is deeply hands-on and focused on backend systems, infrastructure, and distributed execution, with a strong emphasis on performance, scalability, and enterprise readiness. You will be responsible for designing and operating the systems that support multiple customers, multiple deployment models, and an expanding set of evaluation and simulation scenarios. While people management and hiring are nice to have, the priority is technical leadership, architectural judgment, and execution in a fast-moving, customer-facing environment. This role is ideal for someone who has built and operated cloud services at scale and wants to apply that experience to a complex, high-impact AI platform.

Requirements

7–10+ years of experience building backend systems, platforms, or cloud services.
Strong experience with distributed systems, infrastructure, and cloud-native architectures.
Hands-on experience with: Python (primary language today)
Containers and orchestration (Docker, Kubernetes)
Cloud platforms (AWS, GCP, or Azure)
Experience building or operating B2B SaaS platforms at scale, including multitenancy and reliability concerns.
Comfort working directly with customers in a B2B setting, including handling escalations and ambiguous requirements.
Strong communication skills and sound technical judgment.

Nice To Haves

Experience in cloud or data infrastructure companies (e.g., AWS, GCP, Azure, Databricks, Snowflake, Datadog, Confluent).
Prior experience at an early-stage startup.
Some people management or hiring experience (not required).
Experience working on ML platforms, evaluation systems, or large-scale data pipelines.

Responsibilities

Own the architecture, reliability, and scalability of Collinear’s AI agent improvement product offerings.
Design and operate multi-tenant, distributed backend systems that support enterprise customers.
Make platform-level decisions across infrastructure, runtimes, deployment models, and developer experience.
Translate customer needs and ambiguity into clear engineering priorities and durable platform capabilities.
Partner with founders and research leadership on technical strategy, roadmap, and tradeoffs.
Establish engineering standards and best practices as the platform and team scale.
Hire and mentor engineers over time as the organization grows.