Staff Software Engineer (Platform Architecture & Execution Model)
Red Cell Partners
| Company | Red Cell Partners |
| Category | Engineering |
| Location | Seattle |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 16 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
About Us
Red Cell Partners is an incubation firm building and investing in rapidly scalable technology-led companies that are bringing revolutionary advancements to market in three distinct practice areas: healthcare, cyber, and national security. United by a shared sense of duty and deep belief in the power of innovation, Red Cell is developing powerful tools and solutions to address our Nation’s most pressing problems. About Trase
Co-founded in 2023 by Joe Laws and Grant Verstandig , Trase Systems is AI, Uncomplicated. Trase empowers enterprise leaders to harness the full potential of AI without the associated complexity and risks. We are an end-to-end solution for deploying, managing, and optimizing AI in the enterprise. Our platform specializes in bridging the “last mile” of AI adoption, unlocking AI's full potential while driving efficiency and significant cost savings. Trase is at the forefront of AI Agent innovation, topping the Hugging Face GAIA Leaderboard for Generalized AI Assistants, ahead of industry giants such as Google, Meta, Microsoft, and OpenAI. We are leveraging our cutting-edge technologies to develop mission-critical agentic applications in complex industries such as Healthcare, Oil & Gas, and National Security.
About The Role
As Staff Software Engineer , you’ll own the core execution model and platform architecture of Trase OS - the shared platform (“agentic operating system”) that powers all Trase deployments in regulated environments. You’ll define the abstractions and APIs that connect workflows, agents, tools, and product surfaces, and ensure the correctness, scalability, and extensibility of the system.
This is a company-critical role: you are responsible for how the system behaves under real-world conditions, including failure, scale, and security constraints. Your work sets the technical direction for the platform and acts as a force multiplier across all engineering teams.
Clean abstractions and correctness-under-failure are critical because we operate long-lived agents in healthcare/defense environments where auditability and reliability are non-negotiable.
Why This Role Is Needed
Trase OS is an orchestration-heavy system coordinating long-lived workflows, agents, and tools across multiple services and environments.
As the platform evolves, the primary risks shift from implementation to system design quality:
Poor abstractions create tight coupling across services
Workflow execution becomes difficult to reason about under failure
Platform capabilities fragment instead of becoming reusable primitives
Scaling introduces complexity instead of leverage
This role exists to:
Define clean, durable abstractions for the platform execution model
Ensure correctness and determinism in workflow execution
Translate evolving product requirements into coherent platform architecture
Enable teams to build on Trase OS without introducing systemic complexity
What Makes This Role Hard
You are designing systems where failure is the norm, not the exception, and correctness must be preserved across retries, restarts, and partial execution
You must balance clean abstractions with real-world constraints (performance, security, multi-tenant environments)
Decisions made here become foundational primitives used across all products and teams
The system must remain understandable and auditable, even as complexity and scale increase
Responsibilities
Develop the core execution model (state machine, lifecycle, resource model, failure semantics)
Design platform APIs/SDKs connecting workflows, agents, tools, and product surfaces; drive versioning & compatibility
Guarantee correctness via idempotency, deterministic replays, compensating actions, and data integrity
Engineer reliability at scale: concurrency controls, rate limits, backpressure, sharding/partitioning, and workload isolatio
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