AI Workflow Engineer
Skills
Web ApplicationsAdoptionAnalyticsContextLarge Language ModelsReadinessRewriting
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 2-3+ years hands-on experience building AI or LLM systems in production
- 2+ years designing and operating agentic workflows and pipelines with multi-step orchestration tool use evaluation and governance
- Experience embedded in modern development teams practicing GitOps and CI/CD
- Working knowledge of grounded AI patterns including RAG context engineering structured outputs and observability
- Strong software engineering fundamentals in JavaScript TypeScript and/or Python
- Comfort working with Angular React and Express web applications
- Alignment with continuous delivery culture and operational excellence
- Self-starter bias for action with ability to build measure and share solutions
- Strong communication skills for technical and executive audiences
- Must be authorized to work in the United States and be US-remote
Nice to have
- DevEx mindset
- Platform engineering
- Delivery metrics
- AI governance
- Secure SDLC
Day to day
- Architect an agentic software factory that integrates AI agents into planning building testing reviewing and shipping workflows
- Design and operate grounded trustworthy AI systems with retrieval context and evaluation harnesses that prove reliability
- Establish governance guardrails human-in-the-loop checkpoints audit trails and security controls for responsible adoption
- Formalize repeatable frameworks playbooks and internal platforms to scale AI acceleration across engineering and the organization
- Champion AI adoption by teaching supporting and amplifying the team as a force multiplier