Senior/Staff Software Engineer - Platform and Execution Model

About The Role

As a Senior or Staff Software Engineer, you'll build and own critical parts of Trase OS, the shared platform that powers Trase deployments in regulated environments. You'll work on the distributed systems and platform primitives connecting workflows, agents, tools, and product surfaces, with a particular focus on reliability, scalability, and correctness.

You'll take on technically ambiguous problems, design solutions, and drive them through production. This is a hands-on engineering role for someone who is comfortable going deep on distributed systems while helping other engineers make sound architectural decisions.

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.

The level will reflect your experience and demonstrated scope. Staff-level candidates will be expected to lead architecture across teams, establish engineering standards, and mentor other engineers. 

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:

• Design and implement 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 Challenging

• 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

• Design, build, and own critical components of the core execution model (state machine, lifecycle, resource model, failure semantics)
• Build reliable distributed systems that behave predictably across retries, restarts, partial failures, and concurrent execution.
• Develop 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 isolation
• Build security & governance into the core: RBAC/ABAC, policy enforcement, fine-grained audit & lineage
• Deliver observability: distributed tracing, structured logs, metrics, and evaluation hooks; build an “explainable trail” of agent actions
• Own quality: design reviews, test strategy (unit, property, chaos), performance baselines, SLOs, incident response, and postmortems
• Mentor engineers, contribute to design reviews, and help establish strong engineering patterns across the platform.

Requirements

• 8+ years of experience building distributed/platform systems, including significant experience defining architecture across teams or domains 
• 4+ years owning mission-critical runtimes or workflow/orchestration systems
• Deep expertise with durable execution (e.g., state machines, event sourcing, saga/compensation, idempotency, exactly/at-least-once semantics)
• Proven track record with security & governance in production systems (auth, RBAC, audit, policy)
• Hands-on with observability (Grafana or equivalent), including trace correlation across async boundaries
• Strong systems design across storage, queues, schedulers, and evented architectures; performance tuning under load
• Excellence in a modern language (e.g., Go, Rust, Java, or TypeScript) and cloud-native stacks (containers, CI/CD, IaC)
• Comfortable operating in regulated or high-assurance environments; bias toward correctness, clarity, and documentation
• Strong technical judgment and the ability to influence design decisions within a team and across closely related engineering areas.
• Ability to incorporate advance LLM capabilities into system design and platform architecture decisions where appropriate

Nice to Have

• Prior work on workflow engines (Temporal/Cadence/AWS Step Functions, Argo, Airflow) or serverless runtimes
• Experience with policy engines (OPA), secrets/KMS, or data-handling controls (PII/PHI)
• ML/LLM evaluation frameworks, tool/plugin architectures, or embedding model governance into execution
• Government or healthcare experience (HIPAA, audit readiness) and multi-tenant isolation

If you want to be on the cutting edge of technology, building AI solutions for the future, and are up for a challenge, let’s talk!

Salary Range: $180,000-240,000. This represents the typical salary range for this position based on experience, skills, and other factors.

Some travel to customers may be required.