Principal Software Engineer, Core Experiences (Remote Eligible)

Overview

Principal Software Engineer on Core Views, setting the technical direction for the platform and front end behind Smartsheet's most used work surfaces (sheets, reports, and dashboards), with a focus on how sheet data is stored, served and moved between transactional systems and a lakehouse platform.

What you'll do

• Own the end-to-end design for how sheet data is stored, tiered, and served across transactional databases and the lakehouse platform, including data lifecycle and retention strategy, schema evolution, asynchronous access patterns, and consistency guarantees.
• Shape services and APIs that serve sheet data to a real-time collaborative experience and to AI agents at machine scale, making and documenting trade-offs between latency, consistency, and cost.
• Identify the largest technical opportunities and risks across Core Views and the platforms it depends on, build prototypes to prove them out, and turn them into initiatives leadership will invest in.
• Plan and execute changes to petabyte-scale production data with zero customer impact, including phased cutovers, backfill and reconciliation, verification at scale, and a rollback path for every step.
• Scope multi-quarter efforts into phased plans with clear milestones, track progress across teams, raise risks early and candidly, and ship on time.
• Partner with Product, Data Platform, AI Platform, and Infrastructure to align on direction, influence roadmaps you do not own, and represent Core Views in company-level platform and vendor decisions.
• Write architecture decisions, RFCs, and standards other teams build against, and lead the design reviews that enforce them.
• Define patterns and guardrails for integrating AI capabilities into complex multi-system architectures and into how engineers build software, and measure the impact.
• Solve complex multi-system problems with simple, high-performing code in Java on AWS and Kubernetes, do deep code reviews across product areas, and mentor senior and staff engineers on distributed systems and data-intensive design.
• Participate in on-call, lead the most complex incidents to resolution, investigate database and infrastructure internals to find performance bottlenecks, and drive root-cause work to improve resilience.

What you'll need

• 10+ years building highly scalable, highly available, low-latency systems, including several years operating at Principal or Staff level.
• Production-quality Java or Kotlin, and comfort working across the stack.
• Experience designing and running asynchronous, event-driven systems on AWS or comparable cloud infrastructure, including handling ordering, idempotency, back-pressure, partial failure, and consistency across service boundaries.
• Experience owning systems backed by very large relational or distributed datastores, including tuning, scaling, and moving data off them without customer impact.
• Experience taking a fuzzy, high-stakes technical problem from first prototype to production across multiple teams, with a phased plan, early risk calls, and a demonstrable outcome.
• Experience writing design docs, RFCs, or standards that changed how an engineering organization builds and that held up after you moved on.
• Experience building LLM-enriched workflows that delivered measurable value to SaaS customers.
• A degree in Computer Science, Engineering, or a related field, or equivalent practical industry experience.
• Legally eligible to work in the U.S. on an ongoing basis.

Nice to have

• Databricks (Delta Lake, Unity Catalog, Spark) or comparable lakehouse experience such as Snowflake or Apache Iceberg.
• Streaming platforms such as Kafka or Kinesis.
• Building data access for AI agents, such as MCP servers or agent-facing APIs.
• Real-time collaborative applications.

Details

• Remote eligible: may work from anywhere in the US where Smartsheet is a registered employer, or report to the Sr. Director of Engineering in the Bellevue, WA office.
• US base salary range: $205,000 to $275,000 USD, plus a market competitive incentive opportunity; actual compensation depends on experience, skills, education and candidate location.