AI Workflow Architect

Overview We are seeking a forward-thinking AI Workflow Architect to design and implement scalable AI-powered workflows across business units. This role combines deep technical knowledge of AI / ML technologies with a strong understanding of business processes to architect intelligent systems that improve efficiency, reduce operational friction, and unlock new capabilities across the enterprise.

You will serve as a key link between technical engineering teams, data scientists, and business stakeholders to build AI-driven automation pipelines, orchestration layers, and decision systems. You’ll also be responsible for ensuring governance, scalability, and sustainability of these workflows.

Responsibilities Architect end-to-end AI workflows from data ingestion to model deployment and decision-making.

Design orchestration strategies using tools like Airflow, Prefect, or custom solutions.

Define interfaces between AI models, APIs, business logic, and human-in-the-loop components.

Integrate AI systems into business operations using APIs, RPA tools, and platform-specific SDKs (e.g., OpenAI, Google Vertex, Azure AI).

Collaborate with IT and DevOps teams to embed workflows within enterprise software ecosystems (CRM, CMS, DAM, ERP).

Partner with product, marketing, operations, and engineering teams to identify automation opportunities.

Translate business needs into technical solutions and ensure successful stakeholder adoption.

Establish monitoring, auditing, and fallback mechanisms to ensure reliability and ethical use of AI.

Define and enforce best practices around model versioning, data privacy, explainability, and human oversight.

Stay updated with the latest trends in generative AI, workflow orchestration, and MLops.

Recommend emerging tools and platforms that align with strategic AI goals.

Required Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Data Engineering, or related field.

5+ years of experience in software architecture, AI engineering, or automation design.

Hands-on experience with AI / ML lifecycle tools (e.g., MLflow, LangChain, Hugging Face).

Strong understanding of workflow orchestration systems (e.g., Apache Airflow, Kubernetes, Zapier, n8n).

Familiarity with large language models (LLMs), computer vision, NLP, and multimodal AI applications.

Proficiency in Python, APIs (REST / GraphQL), and cloud infrastructure (AWS, GCP, Azure).

Preferred Qualifications Experience with RPA platforms (UiPath, Automation Anywhere) and enterprise integrations.

Exposure to low-code / no-code automation platforms.

Experience with prompt engineering and fine-tuning LLMs.

Knowledge of data governance, security, and ethical AI principles.

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