Member of Technical Staff

3 months ago

Toronto, CanadaStaff+

Responsibilities

Own a core platform area end-to-end, including design, implementation, operations, and long-term technical direction.
Build and operate a cross-portfolio data lake, feature and semantic layers, tenant-isolated ingestion pipelines, and canonical data models.
Develop reliable backend services, identity and access controls, audit systems, workflow orchestration, APIs, and SDKs.
Design multi-tenant data, compute, and credential isolation across AWS and Azure, including regional residency support.
Build workflow and action runtimes with typed actions, idempotency, retries, rollback paths, approval gates, and audit trails.
Create observability and evaluation infrastructure including traces, metrics, structured logs, replay systems, regression suites, and safe A/B testing.
Design autonomy tiers, kill switches, blast-radius limits, and audit surfaces to protect portfolio companies from unsafe actions.
Support ML- and agentic systems on a reliable foundational platform.

Staff- or principal-equivalent senior engineering depth with experience building and operating systems that real businesses depend on.
Proficiency writing clean, idiomatic code in at least one of Python, Go, Rust, or TypeScript, with the ability to work across these languages.
Practical distributed-systems experience, including idempotency, partial failure, retry semantics, eventual consistency, schema evolution, and multi-tenant isolation.
Experience building or operating non-trivial modern data infrastructure using technologies such as Kafka, Spark, dbt, Iceberg, Snowflake, Databricks, or BigQuery.
A platform mindset focused on usable APIs, documentation, migration paths, and developer experience.
Ability to make architectural decisions in an ambiguous, evolving product and platform environment.
Interest in modern ML and the ability to build infrastructure around models; ML research expertise is not required.
Prior Staff or Principal Engineer experience, large-scale Iceberg, Polaris, Snowflake, or Databricks experience, multi-tenant SaaS or platform infrastructure experience, production LLM systems experience, applied research in offline RL or contextual bandits, and open-source contributions are bonus qualifications.