Staff Engineer

What you'll do

Personalization (primary focus)

- Set technical direction for personalization-service (NestJS/TypeScript, MongoDB, Apollo GraphQL federation), including the real-time trait ingestion and activation-hub re-architecture

- Design and review the systems that power Switchboard, our internal targeting and config layer built on top of Statsig, for personalized slot delivery

- Own the hard technical calls on trait ingestion and activation logic that feeds real-time personalization decisions across buyer surfaces

- Guide transactional email personalization (Knock) architecture for order confirmations, shipment updates, and lifecycle messaging

- Set standards for how personalization services work within the WunderGraph federation gateway and JWT sidecar

- Partner with Product and the Personalization Lead on technical strategy, and review designs and code across the squad to keep the bar high

- Mentor L3/L4 engineers on the team and represent Personalization in cross-squad technical discussions, including with Intelligence

Agentic development

- Use AI coding agents (Claude Code, Cursor, or similar) daily to accelerate feature work, technical design, and code review

- Write and maintain agent-readable context files (CLAUDE.md, AGENTS.md) and skills that encode personalization-service conventions so agents produce code that passes review

- Define guardrails and scaffolding that keep agent-generated code aligned with our architecture, testing, and data-handling standards

- Evaluate agent output quality, iterate on prompts and workflows, and bring a point of view on where agentic tooling fits into the team's day-to-day

- Mentor other engineers on the squad in using agentic tooling effectively Intelligence (cross-squad support)

- Pitch in on marketing attribution and enhanced conversion tracking work, primarily dbt models running against Snowflake

- Support CDP (Segment) event and trait governance, including schema and model changes in dataengineering-dbt-segment

- Help triage data quality issues flagged by Monte Carlo observability monitors

- Contribute to Unified Account data model work as capacity allows

What you'll bring

Required

- 8+ years of back-end software engineering experience, including time operating at a staff-level scope (driving architecture and technical direction, not just executing tickets)

- Strong TypeScript/Node.js experience; comfort with NestJS or a similar framework, and building/maintaining REST or GraphQL APIs in production (Apollo federation a plus)

- Hands-on daily use of AI coding agents (Claude Code, Cursor, or similar), including writing context files, skills, or rules that shape agent output

- Solid experience with MongoDB or a similar document store

- Familiarity with containerized deployments (Docker, Kubernetes) and infrastructure as code (Terraform)

- Strong debugging instincts in distributed, service-oriented systems

- Track record of mentoring engineers and reviewing designs/code at a high bar

Nice to have

- Comfort reading and writing SQL against a modern cloud data warehouse (Snowflake) and exposure to dbt/ELT pipelines

- Experience with event-driven architectures or CDPs (Segment or similar), and familiarity with marketing attribution or adtech concepts

- Experience with feature flagging or experimentation platforms (Statsig, LaunchDarkly)

- Experience with GraphQL federation (Apollo, WunderGraph)

- Background in personalization, recommendation systems, or martech

What this role is not

This is not a people-management role - staff here means technical scope and influence, not direct reports. It's also

not a full-time data engineering role: Personalization is home base and where most of your time goes, and the

Intelligence work is a cross-squad contribution, not a pipeline you own end to end. If you want a role that combines

deep technical ownership, hands-on agentic development, and enough range to flex into the data side of MarTech,

this is that role.