AI Workflow Engineer/Remote

Job Description- AI Workflow Engineer

We are looking for an AI Workflow Engineer to design, build, and optimize AI-powered workflows and automation systems. The role involves integrating AI models, APIs, and enterprise tools to create scalable and efficient end-to-end workflows that improve business operations and user experiences.

Key Responsibilities

• Design and implement AI-driven workflows and automation pipelines.
• Integrate LLMs, APIs, databases, and third-party platforms into workflows.
• Build orchestration logic for AI agents and task automation systems.
• Develop backend services and workflow APIs using Python.
• Optimize workflow performance, reliability, and scalability.
• Monitor, debug, and maintain AI workflow systems in production.
• Collaborate with product, engineering, and AI teams to deliver solutions.
• Implement logging, observability, and workflow governance practices.

Required Skills

• Strong proficiency in Python.
• Experience with workflow automation and orchestration tools.
• Understanding of AI/ML concepts and LLM-based applications.
• Familiarity with agent frameworks such as LangChain, CrewAI, LangGraph, or similar.
• Experience with REST APIs and backend development.
• Knowledge of databases such as PostgreSQL, MongoDB, or Redis.
• Strong debugging and problem-solving abilities.

Preferred Qualifications

• Experience with cloud platforms like AWS, Google Cloud Platform, or Azure.
• Familiarity with vector databases and RAG architectures.
• Knowledge of Docker, Kubernetes, and CI/CD pipelines.
• Experience with FastAPI or Flask.
• Exposure to observability and monitoring tools.

Nice to Have

• Experience building multi-agent or autonomous AI systems.
• Knowledge of async programming and distributed workflows.
• Understanding of AI safety, governance, and evaluation methods.
• Familiarity with event-driven architectures and message queues.

Tools & Technologies

Python, FastAPI, LangChain, LangGraph, CrewAI, OpenAI APIs, PostgreSQL, Redis, Docker, Kubernetes, AWS/Google Cloud Platform, Vector Databases, Git.