Staff AI Marketing Systems Engineer

Accountabilities:

• • Discover and map Sales and Marketing workflows by working directly with sellers, product marketing managers, and campaign teams to identify inefficiencies, requirements, and opportunities for AI-driven improvement.
  • Define agent runtime and application architecture covering context, state, tools, permissions, retrieval, evaluation, human review, routing, and execution.
  • Design trusted knowledge flows that combine account, persona, product, competitive, and campaign intelligence while managing freshness, conflicting sources, provenance, and source-of-truth decisions.
  • Build routing systems and specialist agents supporting sales asset generation, campaign briefs, competitive intelligence, copy production, account planning, and active deal workflows.
  • Integrate AI capabilities with enterprise Sales and Marketing platforms such as Salesforce, Seismic, Gong, Notion, Snowflake, and Slack, while maintaining appropriate access boundaries.
  • Establish permission-aware retrieval, audit trails, provenance, prompt-injection defenses, retention controls, and clear rules for autonomous versus human-approved actions.
  • Develop evaluation frameworks, regression testing, release checks, and quality guardrails to ensure AI outputs are accurate, relevant, reliable, on-brand, and useful.
  • Continuously evaluate agent performance using seller feedback, usage data, output quality metrics, and representative evaluation sets, improving prompts, retrieval, tools, models, and workflows.
  • Own systems throughout their lifecycle, from rapid prototype through reliable production deployment, monitoring, optimization, and eventual retirement.
  • Track workflow outcomes including time-to-information, content creation effort, editing requirements, adoption, response time, cost per request, citation coverage, source freshness, and output accuracy.
  • Partner closely with Sales leadership, Marketing Operations, Data, Security, IT, Engineering, and other stakeholders to translate business needs into scalable technical solutions.

  Requirements:

  • 6+ years of experience designing, building, and operating production AI systems that use LLM APIs, tool calling, retrieval, structured outputs, and agent workflows.
  • Demonstrated experience shipping AI-enabled software that real users depend on, with the ability to explain what was built, how it was evaluated, what failed, and how it was improved.
  • Strong knowledge of agent-system architecture, including agent boundaries, context and state management, permission-aware tools, evaluation, observability, failure handling, and human escalation.
  • Experience with modern AI development tools and frameworks such as Claude, Codex, Cursor, Dust, LangChain, LangGraph, or comparable technologies.
  • Strong technical judgment and the ability to determine when a problem is best solved with deterministic code, workflows, retrieval, a single agent, multiple agents, or human review.
  • A strong builder mindset, with a preference for rapidly prototyping with users and converting successful experiments into maintainable production capabilities.
  • Experience creating evaluation frameworks using prompt evaluations, output scoring, regression testing, and verified examples to measure agent quality.
  • Strong user-centered product instincts and experience gathering feedback, iterating quickly, and translating real-world workflows into technical requirements.
  • Excellent cross-functional communication skills, with the ability to work effectively with sellers, marketers, engineers, data teams, security teams, and other stakeholders.
  • Ability to clearly communicate architecture, technical tradeoffs, workflow constraints, and product decisions to both technical and non-technical audiences.
  • Preferred experience with B2B SaaS sales and marketing workflows, including personas, buying stages, positioning, competitive intelligence, campaigns, sales enablement, and content governance.
  • Familiarity with platforms such as Salesforce, Seismic, Gong, Notion, Snowflake, or Slack APIs, as well as iPaaS and cross-system automation tools, is a plus.

  Benefits:

  • US base salary: $139,000–$202,000 USD annually.
  • Equity grant and, where applicable, participation in incentive programs.
  • Comprehensive health and dental benefits.
  • 401(k) and retirement matching program.
  • Generous paid time off and paid parental/maternity leave programs.
  • Remote-first work environment within the US, with travel for team meetings, department offsites, and other in-person engagements as applicable.
  • RSU program for most employees.
  • Free access to the company's password-management product.
  • Paid volunteer days and peer-to-peer recognition programs.
  • Opportunities to work with cutting-edge AI technologies and shape production AI systems.
  • Collaborative culture emphasizing clear communication, continuous feedback, experimentation, adaptability, and meaningful impact.