Senior Backend Engineer — Core Platform

Aurora United State
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AI Summary

Design and maintain core APIs, backend services, and workflow orchestration for enterprise document processing systems. Own data modeling, infrastructure, and operational reliability across Python, Kubernetes, and Temporal. Requires strong Python experience, workflow engine knowledge, and customer-facing problem solving.

Key Highlights
Ownership of core APIs, backend services, and workflow orchestration using Temporal
Experience with Python, Kubernetes, Terraform, and Postgres in production systems
Direct customer interaction to translate feedback into backend improvements
Key Responsibilities
Design and ship core APIs with attention to clarity, versioning, validation, and operational safety
Build and maintain backend services supporting document ingestion, extraction, and agent-oriented workflows
Use Temporal for workflow orchestration including retries, long-running jobs, idempotency, backfills, and failure recovery
Shape Postgres schemas and backend data structures to maintain product consistency as usage grows
Work across Python, Kubernetes, and Terraform to keep the platform deployable, understandable, and maintainable
Improve observability, debugging, and incident response for operational reliability
Turn customer feedback into backend changes that improve real deployment behavior
Move quickly from prototype to production and harden systems once patterns are proven
Technical Skills Required
Python Kubernetes Temporal Postgres
Benefits & Perks
Comprehensive medical, dental, and vision coverage
Unlimited PTO
Daily catered in-office lunch

Job Description


Senior Backend Engineer — Core Platform


San Francisco, CA · Hybrid (M/W/F in office) · Full-time


$180K–$250K base + 0.1%–0.4% equity



The company


The company builds infrastructure for developers who want to create agents over complex enterprise documents.


Its open-source framework has more than 4M monthly downloads, and the cloud product has already processed 200M+ documents.


That combination matters: the team sees what developers build in the open, then turns that usage into production cloud workflows used by enterprises.


The company was founded in 2022, has a team of about 40 people, and has raised $27.5M.


This is a product with real adoption, real usage patterns, and real infrastructure pressure, not an early prototype looking for its first signal.



The role


This is a backend role for someone who wants ownership of the systems behind the product: core APIs, backend services, workflow orchestration, data modeling, reliability, and infrastructure.


You will work across engineering and product, and you will also talk directly to customers when the fastest path to a better product is understanding how they actually use it.


The expectation is not just to ship features. The expectation is to take backend problems from prototype to production and keep them healthy as usage grows.



The technical problem


Enterprise document workflows are messy by default.


Inputs are inconsistent. Processing steps are long-running. Failure modes are non-trivial. State needs to be durable. APIs need to stay stable while the product evolves.


The hard part is building backend systems that can support developer adoption, enterprise reliability, and fast iteration without creating a brittle platform.



What you'll own


• Core APIs: design and ship the interfaces that power the product, with attention to clarity, versioning, validation, and operational safety.

• Backend services: build and maintain services that support document ingestion, extraction, and agent-oriented workflows.

• Workflow orchestration: use Temporal to handle retries, long-running jobs, idempotency, backfills, and failure recovery in production.

• Data modeling: shape Postgres schemas and backend data structures so product behavior stays consistent as usage and complexity increase.

• Infrastructure: work across Python, Kubernetes, and Terraform to keep the platform deployable, understandable, and maintainable.

• Operational reliability: improve observability, debugging, and incident response so issues are found and resolved quickly.

• Product iteration: turn customer feedback into backend changes that improve how the system behaves in real deployments.

• Prototype-to-production ownership: move quickly when the answer is not yet obvious, then harden the system once the pattern is proven.



Who this is for


You are likely a strong fit if you have:


• Owned backend systems end to end, not just shipped tickets inside someone else’s architecture.

• Experience writing production systems in Python.

• Practical judgment around APIs, data models, and the tradeoffs between speed, correctness, and maintainability.

• Experience with workflow engines or async systems, and an understanding of where they fail in practice.

• Built systems that required real operational discipline: monitoring, alerting, rollback planning, and incident follow-through.

• Comfort working on products used by external developers or enterprise customers.

• The ability to talk to users, extract signal from messy feedback, and turn it into technical decisions.

• A preference for owning a hard backend problem deeply rather than scattering across unrelated feature work.



Tech stack


• Backend: Python, Node.js

• Infrastructure: Kubernetes, Terraform

• Data: Postgres

• Workflows: Temporal



Why now


The company already has meaningful open-source adoption and cloud usage. That changes the backend problem from “can we build it?” to “can we make it reliable, observable, and extensible at scale?”


The next stage is about tightening the core platform: cleaner APIs, stronger workflow execution, better data discipline, and fewer production surprises.


This is a good time to join if you want your design choices to matter for years, not quarters.



This role is not for you if


• You want a narrowly scoped feature role with clean requirements.

• You prefer to avoid customer conversations.

• You are uncomfortable owning infrastructure and application behavior together.

• You want a system that is already fully defined.

• You are not interested in the tradeoffs that come with production workflow systems.



Compensation and logistics


• Base salary: $180K–$250K

• Equity: 0.1%–0.4%

• Location: San Francisco, CA

• Work model: hybrid, M/W/F in office

• Visa support: H1B transfers and TN visas supported; new H1B sponsorship is not currently available

• Employment: full-time

• Benefits: comprehensive medical, dental, and vision coverage; unlimited PTO; daily catered in-office lunch



Interview process


• Hiring manager call — 30 min: background, scope, and what you want to own.

• Technical screen — 1 hour: backend depth, systems thinking, and practical judgment.

• On-site interview — 4 hours: remote or in-person in San Francisco.



About Aurora


Aurora helps exceptional engineers find the right role at some of the most ambitious startups worldwide.


We work with teams that value high ownership, strong technical standards, and clear scope.


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