Long Term Evolution Jobs (NOW HIRING)

What You Will Own

• Design and evolve platform-level infrastructure architecture, helping core systems become scalable, maintainable, and reusable.

• Build and improve backend services, data and workflow infrastructure, platform APIs, internal tools, and automation systems.

• Define system boundaries, data contracts, metadata, permissions, observability, and operational patterns across infrastructure components.

• Handle reliability, consistency, scalability, lifecycle management, and failure recovery across batch, service, and platform workflows.

• Collaborate with product, business, operations, data, and research partners to turn incomplete requirements into practical system designs and delivery paths.

• Identify where problems should be solved through platform abstractions and where they should stay simple, balancing architecture quality with delivery speed.

What We Look For

• Strong engineering fundamentals and the ability to own a complex infrastructure or platform direction, beyond a local module.

• Strong Python or backend engineering ability, including services, data processing, platform tooling, automation, and internal APIs.

• Mature architecture judgment around service boundaries, state management, data flow, reliability, observability, and evolution paths.

• Experience or strong understanding of infrastructure for data-heavy systems, including ingestion, storage, querying, metadata, governance, or access layers.

• Clear technical sense, product sense, and communication skills: you can identify the real problem, align tradeoffs, and drive implementation.

• High standards for engineering quality, including tests, refactoring, documentation, and fixing systemic issues instead of only making things run once.

Tech Stack You May Work With

• Python

• Backend services, platform APIs, and infrastructure automation

• Data processing workflows, storage, query, and access-layer design

• Metadata, schema evolution, permissions, governance, and lifecycle management

• Docker, CI/CD, observability, internal tooling, and engineering infrastructure

Bonus Points

• Experience building platform products, developer platforms, data infrastructure, or complex internal infrastructure systems.

• Experience with ingestion frameworks, metadata systems, access control, multi-tenant platforms, or query/service layers.

• Experience with AI agent harnesses, automation workflows, or platform tooling.

• Experience driving complex migrations, architecture convergence, or platform refactors without disrupting production users.

• Ability to understand systems across the stack, even if this role is not centered on frontend development.

This Role May Not Be a Fit If

• You prefer clearly specified tasks and do not want to make architecture or product tradeoffs.

• You are comfortable owning a narrow technical slice but do not want to own system-level complexity and long-term evolution.

• You respond to ambiguous problems mainly by adding more code instead of clarifying abstractions, boundaries, and ownership.

• You do not enjoy communicating with cross-functional partners or understanding the business context behind the system.

• You optimize locally without caring about platform consistency, maintainability, and long-term cost.

Why This Role Matters

This role has meaningful architecture ownership. We are looking for someone who can help shape the foundation of our infrastructure. You will influence how systems scale, how data and workflows are organized, how the platform supports future product directions, and how the team solves complex problems with high engineering quality. For the right person, this is a role with deep ownership across architecture, product judgment, and system evolution.

What We Would Like to See When You Apply

• Real systems or infrastructure areas you have owned, not limited to demos or isolated features.

• Examples of how you made architecture decisions, handled complex system boundaries, controlled complexity, and delivered production outcomes.

• Examples of how you approached data movement, metadata, governance, platform abstractions, or other long-term infrastructure problems.

• If relevant, examples of AI agent harnesses, automation systems, or platform tooling that show your technical sense, communication, and product judgment.