Senior Engineer, Enterprise Platforms

Abnormal AI · Vertical AI · United States · Remote · IT

Senior Engineer, Enterprise Platforms to build and operate AI agents, copilots, and automations for IT and security functions. The role involves turning policies into AI workflows, integrating with enterprise platforms, and ensuring governance, evaluation, and observability for AI services.

What you'd actually do

  1. Design and ship AI agents and copilots for Enterprise Platforms that automate joiner mover leaver flows, access requests, troubleshooting, and governance reviews
  2. Wrap existing runbooks and policies in AI powered workflows across internal tools, automations, and conversational interfaces
  3. Build safe data and integration layers for AI using platform APIs, logs, and internal knowledge content, including retrieval augmented patterns where appropriate
  4. Implement prompts, tools, and orchestration flows with clear guardrails, access controls, approvals, and audit trails so governance is built in
  5. Add evaluation, logging, and monitoring so AI features can be tested, rolled out, and debugged like any other production service

Skills

Required

  • platform or systems engineering
  • automation
  • code structures, APIs, and integration patterns
  • large language models and practical AI application design
  • prompts, tools, guardrails, and evaluation
  • AI or automation workflows that integrate with enterprise platforms
  • read and reason about code and automation frameworks
  • identity and access concepts
  • observability practices
  • incident and change management habits
  • written and verbal communication

Nice to have

  • remote first and SaaS heavy environments
  • zero trust concepts
  • building or operating internal copilots, workflow or conversational interfaces, or agents for IT, security, or operations teams
  • AI orchestration or workflow systems
  • evaluation methods such as golden sets or human review
  • security and compliance frameworks such as SOC 2 or ISO 27001
  • mentoring others or leading technical work

What the JD emphasized

  • ownership of complex, connected systems
  • Hands on experience building or operating AI or automation workflows
  • Comfort with observability practices
  • Proven incident and change management habits

Other signals

  • AI agents and copilots
  • AI powered workflows
  • retrieval augmented patterns
  • prompts, tools, and orchestration flows
  • evaluation, logging, and monitoring for AI features