Job Type: Full-time

What you'll doPersonalization (primary focus)Set technical direction for the personalization service (NestJS/TypeScript, MongoDB, Apollo GraphQL federation), including the real-time trait ingestion and activation-hub re-architectureDesign and review the systems that power Switchboard, our internal targeting and config layer built on top of Statsig, for personalized slot deliveryOwn the hard technical calls on trait ingestion and activation logic that feeds real-time personalization decisions across buyer surfacesGuide transactional email personalization (Knock) architecture for order confirmations, shipment updates, and lifecycle messagingSet standards for how personalization services work within the WunderGraph federation gateway and JWT sidecarPartner with Product and the Personalization Lead on technical strategy, and review designs and code across the squad to keep the bar highMentor L3/L4 engineers on the team and represent Personalization in cross-squad technical discussions, including with IntelligenceAgentic developmentUse AI coding agents (Claude Code, Cursor, or similar) daily to accelerate feature work, technical design, and code reviewWrite and maintain agent-readable context files (CLAUDE.md, AGENTS.md) and skills that encode personalization-service conventions so agents produce code that passes reviewDefine guardrails and scaffolding that keep agent-generated code aligned with our architecture, testing, and data-handling standardsEvaluate 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-dayMentor other engineers on the squad in using agentic tooling effectivelyIntelligence (cross-squad support)Pitch in on marketing attribution and enhanced conversion tracking work, primarily dbt models running against SnowflakeSupport CDP (Segment) event and trait governance,



including schema and model changes in dataengineering-dbt-segmentHelp triage data quality issues flagged by Monte Carlo observability monitorsContribute to Unified Account data model work as capacity allowsWhat you'll bringRequired8+ 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 outputSolid experience with MongoDB or a similar document storeFamiliarity with containerized deployments (Docker, Kubernetes) and infrastructure as code (Terraform)Strong debugging instincts in distributed, service-oriented systemsTrack record of mentoring engineers and reviewing designs/code at a high barNice to haveComfort reading and writing SQL against a contemporary cloud data warehouse (Snowflake) and exposure to dbt/ELT pipelinesExperience with event-driven architectures or CDPs (Segment or similar), and familiarity with marketing attribution or adtech conceptsExperience with feature flagging or experimentation platforms (Statsig, LaunchDarkly)Experience with GraphQL federation (Apollo, WunderGraph)Background in personalization, recommendation systems, or martechWhat this role is notThis 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.

📌 Staff Back-End Engineer (Mumbai)
🏢 Canterr
📍 Mumbai