Description We're seeking an AI Workflow Engineer to join a newly formed team focused on advancing internal AI and LLM platforms. In this role, you'll collaborate with technical colleagues across multiple departments, helping design and build agentic workflow systems and business logic orchestration powered by leading AI solutions.
We're looking for professionals with a development background (Python, Node.js, or similar) who are passionate about moving beyond traditional model training and instead want to tackle applied business applications of AI. You'll be responsible for writing code to coordinate workflows, integrate data sources, and support sophisticated agentic architectures. Experience working with orchestration tools (n8n), integration frameworks, Retrieval-Augmented Generation (RAG), and MCP tools is a big plus.
Your work will involve:
- Developing AI-driven workflows and conversational agents that connect with internal and external data sources
- Working hands-on with code-even if some tasks use low-code or no-code platforms
- Implementing and optimizing solutions for applied data science challenges
- Reviewing, improving, and championing future initiatives based on evolving business requirements
Ideal candidates have worked directly with AI or LLM platforms, possess strong development or applied machine learning experience, and are comfortable in fast-moving, innovative environments. Familiarity with NVIDIA-backed infrastructure is desirable but not required.
If you're excited about shaping agentic AI solutions, integrating business logic, and driving new workflows, we encourage you to apply.
Requirements Proficiency in programming with Python and/or Node, with a focus on clean design and efficient implementation.
Hands-on experience integrating AI systems, including prompt engineering, tool usage, and function calling.
Expertise in building AI workflows and working with vector databases for data retrieval and optimization.
Familiarity with orchestration tools such as LangGraph, CrewAI, or n8n to streamline workflow development.
Experience in developing secure AI tools and servers for seamless integration with APIs and databases.
Solid understanding of GraphQL, OAuth authentication, and secure system integration.
Knowledge of containerization, Git, and CI/CD practices to ensure reliable deployment of AI services.
Practical experience in implementing safety measures, evaluation protocols, and compliance standards for AI solutions.
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