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Included Health

Staff AI Solutions Engineer

Included Health
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about 3 hours ago
Remote, United StatesStaff+
H1B Sponsor

Responsibilities

  • Design, build, deploy, and maintain production LLM-based solutions and agent workflows.
  • Own the technical strategy and reference architecture for enterprise AI solutions.
  • Lead high-complexity, cross-functional AI initiatives from problem definition to production adoption.
  • Define and evolve reusable platform capabilities and implementation standards.
  • Review citizen developer AI agents for optimization and compliance.
  • Influence roadmap and investment decisions through technical leadership.
  • Drive technical debates and align stakeholders on tradeoffs.
  • Implement, review, and validate code produced by models.
  • Build integrations and connectors between AI tooling and enterprise SaaS.
  • Own end-to-end deployment and lifecycle for AI services.
  • Establish and operate model evaluation and monitoring.
  • Lead vendor evaluations and POCs for LLM/agent platforms.
  • Partner with Cybersecurity and Compliance for data handling patterns.
  • Create and maintain architecture diagrams and documentation.
  • Mentor engineers and influence architectural standards.
  • Drive automation of operational tasks via agents and workflow tooling.
  • Partner with Technology Services leadership for AI spend management.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
  • 8+ years of professional software engineering or systems integration experience.
  • Practical experience owning the complete lifecycle of LLMs and agents.
  • Experience evaluating model performance and implementing human-in-the-loop controls.
  • Ability to define reference architectures for AI services.
  • Experience making architectural tradeoffs in production systems.
  • Strong coding experience in Python and/or TypeScript/JavaScript.
  • Experience designing and building API integrations and custom connectors.
  • Experience with Infrastructure as Code (Terraform) and cloud deployment.
  • Familiarity with CI/CD tooling and observability best practices.
  • Working knowledge of security best practices for data-sensitive systems.
  • Strong communication and collaboration skills.