AI Engineer
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Job Description
AI Engineer building production multi-agent AI systems for an organization automating knowledge-based workflows. Owning RAG, integrations, cloud deployment, monitoring, security, and governance end to end.
Responsibilities:
- Design, build, and maintain production-ready multi-agent AI systems
- Develop AI solutions that automate research, content, and business development workflows
- Architect scalable agent workflows with human oversight and governance
- Own AI systems from architecture and development through deployment, integration, monitoring, maintenance, and continuous improvement
- Build and maintain Retrieval-Augmented Generation systems using vector databases, embeddings, semantic search, and retrieval optimization
- Integrate AI systems with business platforms through APIs and webhooks, including CRM, communication, scheduling, and content platforms
- Build human-in-the-loop approval workflows for external-facing AI actions
- Implement logging, monitoring, audit trails, role-based access controls, encryption, and secure cloud infrastructure
- Deploy and maintain AI applications in secure cloud environments
- Build CI/CD workflows, containerized deployments, production monitoring, debugging, observability, and reliability practices
- Work directly with leadership to translate business requirements into reliable AI solutions
- Partner with external developers or technical vendors when needed while serving as the internal technical owner
Requirements:
- Several years of professional software engineering experience
- Recent hands-on experience building and deploying LLM-based or agentic AI systems into production
- Experience owning technical systems from architecture and development through deployment and ongoing maintenance
- Ability to independently design, build, and maintain production applications
- Strong Python programming experience for production-ready AI applications
- Hands-on experience with LangGraph, LangChain, or similar AI agent and workflow orchestration frameworks
- Understanding of event-driven architectures
- Strong experience with LLM APIs, prompt engineering, tool calling, structured outputs, and AI evaluation methods
- Ability to build and consume REST APIs, webhooks, and third-party integrations
- Hands-on experience implementing RAG systems using vector databases, embeddings, semantic retrieval, and retrieval quality evaluation
- Ability to monitor, troubleshoot, and debug production AI applications
- Experience deploying applications using AWS, GCP, or similar cloud infrastructure
- Understanding of CI/CD pipelines, containerization, secure data handling, and production monitoring
- Ability to design AI systems with human-in-the-loop controls, logging, auditability, security, and governance
- Strong professional English communication skills
- Availability to work 9:00 AM–5:00 PM EST / U.S. business hours
- Preferred: experience in regulated industries such as healthcare, finance, or insurance
- Preferred: experience with HIPAA, SOC 2, or similar audit and compliance requirements
- Plus: experience integrating CRM and marketing platforms with AI-powered systems
- Plus: experience with voice AI or conversational AI systems
- Required application materials: English PDF resume and a video showcasing skill sets
Benefits:
- Fully remote work arrangement
- Opportunity to become the technical owner of an organization's AI transformation
- Opportunity to work closely with leadership and contribute to the organization's AI direction
- Opportunity to build systems with significant long-term impact
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