AI Engineer – Marketing Operations

Cyera Cyera · Vertical AI · United States · Remote · Marketing

AI Engineer role focused on building and deploying LLM-powered applications and automation systems within marketing and revenue technology stacks. Responsibilities include designing AI-powered workflows, RAG architectures, and integrating systems, with a focus on productionizing these systems and establishing governance and optimization.

What you'd actually do

  1. Design and deploy AI-powered applications embedded within marketing and CRM infrastructure
  2. Build and productionize LLM-driven workflows, agentic systems, and retrieval-augmented (RAG) architectures
  3. Architect secure integrations across Salesforce, marketing automation platforms, data warehouses, and external APIs
  4. Develop scalable orchestration frameworks for AI workflows (event-driven, API-based, and automation-triggered systems)
  5. Implement monitoring, logging, evaluation, and guardrails for production AI systems

Skills

Required

  • Python
  • SQL
  • LLM APIs
  • vector databases
  • embeddings
  • RAG architectures
  • APIs
  • webhooks
  • event-driven frameworks
  • AWS
  • GCP
  • Azure
  • system design
  • security
  • reliability

Nice to have

  • Marketo
  • HubSpot
  • Pardot
  • Salesforce
  • Tableau
  • Looker
  • Power BI
  • Clay
  • Snowflake
  • BigQuery
  • Segment
  • CDPs
  • Outreach
  • Salesloft
  • Zapier
  • Workato
  • Hightouch
  • Census
  • dbt
  • marketing lifecycle management
  • attribution workflows
  • lead routing logic
  • revenue operations processes

What the JD emphasized

  • production environments
  • production AI systems
  • productionize LLM-driven workflows

Other signals

  • building scalable, production-grade AI systems
  • applied AI — designing, integrating, and operationalizing AI systems
  • LLM-powered applications and automation systems in production environments