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CertifyOS is building data infrastructure for modern healthcare, solving fragmented provider data challenges through an API-first platform that automates provider licensing, enrollment, credentialing, and network monitoring.
You will lead support automation initiatives while designing and building AI solutions end-to-end. This is a hands-on engineering role where you identify high-impact support processes, architect AI/automation solutions, and deploy them to production with continuous improvement.
Key responsibilities include:
- Identifying high-impact support processes suitable for AI/automation
- Designing, building, integrating, testing, and deploying AI-powered workflows and agents
- Developing solutions using LLMs, RAG, AI agents, and workflow automation
- Building end-to-end AI pipelines covering knowledge ingestion, orchestration, model execution, tools/actions, evaluation, and production monitoring
- Integrating AI with CRM, ticketing, knowledge bases, and internal tools
- Monitoring AI quality, accuracy, cost, latency, and business impact
- Partnering with Product and Engineering teams on AI-led transformation
Required experience: 3+ years in software engineering, AI/ML, automation, or support technology; 2+ years hands-on Generative AI/LLM application development with production experience; background in automation, integrations, or workflow engineering.
Must-have technical skills: Python and/or JavaScript/TypeScript; LLM APIs and Generative AI application development; RAG, embeddings, and vector databases; AI agents and agentic workflows; end-to-end AI/LLM pipelines; REST APIs, webhooks, SQL, and system integrations; LLM evaluation, observability, and monitoring; production deployment and CI/CD; understanding of customer-support workflows.
Preferred: experience with OpenAI, Anthropic, Claude, Gemini, LangChain/LangGraph, LlamaIndex, n8n/Make/Zapier, vector databases, AWS/Azure/GCP, Docker, and CRM/helpdesk platforms like Zendesk, Salesforce, or Freshdesk.
The ideal candidate is a builder who can demonstrate real AI/automation solutions personally built or led, explain architecture and contributions, and quantify business impact such as automation percentage, ticket deflection, AHT reduction, or cost savings.
