Senior/Staff Software Engineer (Platform and Execution Model)

Description

The company is an incubation firm that builds and invests in fast-scaling technology companies in healthcare, cyber, and national security.

The company was co-founded in 2023. It offers an end-to-end solution for deploying, managing, and optimizing AI in the enterprise, with a focus on the last mile of adoption. It builds mission-critical agent applications for industries such as healthcare, oil and gas, and national security.

You will work on the shared platform behind those deployments in regulated environments. The focus is distributed systems and platform primitives that connect workflows, agents, tools, and product surfaces, with reliability, scalability, and correctness as the priorities.

The work is hands-on. You take on technically unclear problems, design solutions, and carry them into production. Long-lived agents run in healthcare and defense settings, so auditability and reliability are essential, and clean abstractions and correct behavior under failure matter most.

The platform is an orchestration-heavy system that coordinates long-lived workflows, agents, and tools across services and environments. As it grows, the main risk moves from building features to design quality: tight coupling, execution that is hard to reason about under failure, fragmented capabilities, and complexity that grows faster than leverage. This role exists to fix those risks through clean, durable abstractions, correct and deterministic workflow execution, translating product needs into architecture, and letting other teams build without adding systemic complexity.

Failure is normal here, so correctness must hold across retries, restarts, and partial runs. Performance, security, and multi-tenant constraints have to be balanced against clean design. Decisions made here become foundational primitives for every product and team, so the system must stay understandable and auditable as it grows.

Level depends on experience and demonstrated scope. Staff candidates are expected to lead architecture spanning several teams, set engineering standards, and mentor engineers.

Responsibilities

• Design, build, and own the core execution model, covering the state machine, lifecycle, resource model, and failure semantics.
• Build distributed systems that behave predictably through retries, restarts, partial failures, and concurrent runs.
• Guarantee correctness with idempotency, deterministic replay, compensating actions, and data integrity.
• Create platform APIs and SDKs that connect workflows, agents, tools, and product surfaces, and manage versioning and compatibility.
• Scale reliably using concurrency controls, rate limits, backpressure, sharding and partitioning, and workload isolation.
• Build security and governance into the core: RBAC and ABAC, policy enforcement, and fine-grained audit and lineage.
• Add observability: distributed tracing, structured logs, metrics, evaluation hooks, and an explainable trail of agent actions.
• Own quality: design reviews, test strategy (unit, property, chaos), performance baselines, SLOs, incident response, and postmortems.
• Mentor engineers, take part in design reviews, and build strong engineering patterns across the platform.

Requirements

• 8+ years building distributed or platform systems, including meaningful experience defining architecture across teams or domains.
• 4+ years owning mission-critical runtimes or workflow and orchestration systems.
• Deep knowledge of durable execution: state machines, event sourcing, saga and compensation, idempotency, and exactly-once or at-least-once semantics.
• Proven record of security and governance in production: auth, RBAC, audit, and policy.
• Hands-on with observability such as Grafana or similar, including trace correlation across async boundaries.
• Strong design across storage, queues, schedulers, and event-driven architectures, plus performance tuning under load.
• Skilled in a modern language such as Go, Rust, Java, or TypeScript, and in cloud-native stacks: containers, CI/CD, and IaC.
• Able to work in regulated or high-assurance settings, with a focus on correctness, clarity, and documentation.
• Good judgment on technical matters, and skill at shaping design choices in your own team and adjacent engineering groups.
• Able to bring advanced LLM capabilities into system design and platform architecture where they fit.
• Prior work on workflow engines (Temporal, Cadence, AWS Step Functions, Argo, Airflow) or serverless runtimes.
• Experience with policy engines such as OPA, secrets or KMS, or data-handling controls for PII or PHI.
• ML or LLM evaluation frameworks, tool or plugin architectures, or governing embedding models in execution.
• Government or healthcare experience (HIPAA, audit readiness) and multi-tenant isolation.
• Interested in cutting-edge technology and building AI for the future? Get in touch.

Conditions

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

Some travel to customers may be required.

Hiring platforms may check applications for accuracy and fraud, and flagged applications may be declined.

Benefits

• For full-time roles: a career track with potential for rapid advancement as the firm grows.
• Comprehensive health care including medical, dental, and vision, with 100% employer paid premiums for you and your family.
• Paid maternity and paternity for 14 weeks at normal pay.
• Unlimited PTO, with management approval.
• Professional development and continued learning opportunities.
• Optional 401K, FSA, and equity incentives.
• Mental health benefits through a third-party provider.
• Cost-effective GLP-1 solutions through a third-party provider.
• Benefits may differ for each incubation.