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.

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

- Hands-on daily use of AI coding agents (Claude Code, Cursor, or similar).

- 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).

- 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.