AI Engineer (Agentic Workflow Automation)
We are looking for an AI Engineer to design and build intelligent workflow automation systems using modern LLMs, agentic AI, and orchestration frameworks. The role focuses on developing production-ready AI pipelines that automate operational processes, extract and structure information from documents, coordinate multi-step reasoning workflows, and integrate with enterprise systems. You will work closely with business, operations, and engineering teams to identify high-value automation opportunities and transform them into scalable AI-driven solutions.
Responsibilities
- Design and develop AI-powered workflow automation systems using LLMs and agentic architectures
- Build multi-step AI orchestration pipelines using frameworks such as LangGraph, LangChain, or similar tools
- Develop OCR and document intelligence solutions for extracting, validating, and structuring unstructured data
- Integrate AI services with internal systems, APIs, databases, and cloud platforms
- Build retrieval-augmented generation (RAG) systems using vector databases and embedding pipelines
- Design prompt engineering, tool-calling, and memory strategies for autonomous or semi-autonomous AI agents
- Collaborate with stakeholders to translate operational processes into automated AI workflows
- Evaluate model accuracy, reliability, latency, and operational risks in production environments
- Monitor and improve AI system performance, observability, and cost efficiency
- Participate in rapid prototyping, experimentation, and deployment of new AI capabilities
Requirements
- Degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field
- Strong programming skills in Python
- Experience with LLM frameworks such as LangGraph, LangChain, CrewAI, or equivalent technologies
- Familiarity with LLM APIs and modern AI application architectures
- Experience with OCR/document extraction tools such as Azure Document Intelligence or equivalent solutions
- Understanding of vector databases, embeddings, and RAG architectures
- Knowledge of SQL and data processing pipelines
- Familiarity with cloud platforms such as Microsoft Azure
- Experience with Git, Docker, and modern development workflows
- Strong analytical thinking skills and the ability to work independently in ambiguous problem spaces
