Job Description
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.