Senior AI Engineer (Marketing Platforms)

Quick Facts

• Role: Senior AI Engineer (Marketing Platforms)

Description

Build and harden the backend foundation for marketing operations currently running on HubSpot, including integrations to CRM and data systems. You will help design next-generation AI-native capabilities for lead qualification, intelligent routing, and campaign automation while enforcing consent/suppression and ensuring dependable, traceable lead hand-offs. During transition, you will keep HubSpot integrations healthy, triage incidents, and support safe migration using an agentic SDLC workflow.

Responsibilities

• Build a governed single entry point for leads from multiple sources, ensuring validation, de-duplication, consent, and enrichment before reaching downstream systems.

• Create AI-native lead qualification models based on fit and engagement signals; provide explainable scoring and learning from real conversions.

• Implement intelligent lead routing using territory/capacity/availability/priority and decision records for transparency.

• Make lead hand-offs dependable by tracking capture-to-first-touch, surfacing stalls, and enforcing follow-up behavior.

• Provide a self-service campaign layer where per-campaign routing/priority/nurture can be configured quickly with preview and safe override behavior.

• Expose platform data and actions through an MCP server so internal agents can look up leads, explain decisions, and trigger campaign actions in natural language.

• Enforce consent and suppression as a single source of truth, gated and impossible to bypass, and stream signals/decisions into the data master.

• Integrate with upstream/downstream vendor systems with retries and visibility to prevent silent/lossy failures.

• Use an agentic SDLC approach to ship production changes; own code quality/security and continuously document the system.

• Maintain existing HubSpot integrations until retirement; triage root cause, fix permanently, and document incidents.

• Implement a Forms Gateway pull-forward to decouple capture from HubSpot and run an interim enrollment connector for cutover.

• Reconcile HubSpot and platform data continuously during parallel run to detect drift early.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or related technical field.

• 6+ years building and operating production backend systems, including at least 3 years with Python.

• Recent daily practice building with AI coding agents (Claude Code, Cursor, Copilot agent mode, Codex or similar), including the workflow, review/test loop, and real shipped outcome.

• Production support experience for marketing automation platform integrations (HubSpot strongly preferred; Marketo/Pardot considered), including APIs, data model, and CRM sync.

• Production experience with event-driven and durable execution patterns (message queues, outboxes, idempotency keys, replay); Temporal or comparable workflow engine preferred.

• Hands-on integration engineering against real vendor APIs (REST, webhooks, OAuth 2.0, rate limits, retries), built and operated in production.

• Strong PostgreSQL skills: schema design, JSONB, partitioning, Alembic migrations, and query performance.

• Cloud deployment on Azure or AWS: containers, Terraform or Bicep, GitHub Actions CI/CD, secrets management, and observability.

• Experience shipping LLM features into a product: structured outputs, evaluation discipline, confidence thresholds, fallbacks, and guardrails using a provided model gateway.

• Excellent written and spoken English and ability to explain technical trade-offs to marketing operations.

Benefits

• Work on an AI-native marketing platform with end-to-end responsibility for reliability, security, and explainable AI decisioning.