AI Systems Integration Specialist
6 days ago
We are seeking an experienced AI Systems Integration Specialist to lead the design, development, and deployment of AI-driven solutions across enterprise environments. This role requires expertise in integrating AI/ML models, APIs, and platforms into existing business systems, ensuring seamless interoperability, scalability, and performance. You will work closely with cross-functional teams to bridge the gap between data science, software engineering, and enterprise applications.
Key Responsibilities- Architect and implement end-to-end AI system integrations across ERP, CRM, and enterprise platforms.
- Develop and manage APIs, microservices, and middleware to support AI-driven applications.
- Collaborate with data scientists, developers, and product teams to bring AI models into production.
- Ensure system compatibility, data flow, and performance optimization between AI solutions and core IT systems.
- Deploy AI workloads on cloud (AWS, Azure, GCP) and hybrid environments.
- Define and enforce integration standards, security policies, and compliance guidelines.
- Monitor and troubleshoot integration pipelines, ensuring high availability and reliability.
- Provide technical leadership on best practices for AI adoption and integration strategies.
Requirements
Skills & Experience Required- Proven experience as a Systems Integration Specialist, AI Engineer, or Solutions Architect.
- Hands-on expertise in AI/ML model deployment and integration.
- Strong knowledge of APIs, web services (REST, GraphQL), and middleware platforms.
- Proficiency in Python, Java, or with exposure to AI frameworks (TensorFlow, PyTorch, Scikit-learn).
- Experience with ETL pipelines, data engineering, and workflow automation.
- Familiarity with enterprise applications (SAP, Salesforce, Dynamics) and integration tools (MuleSoft, Dell Boomi, Apache Kafka).
- Strong understanding of cloud-native architectures, containers (Docker, Kubernetes), and CI/CD pipelines.
- Excellent problem-solving, documentation, and communication skills.
- Exposure to AI-driven automation and intelligent workflows (e.g., RPA + AI).
- Experience with MLOps tools for monitoring and managing AI models.
- Knowledge of cybersecurity, data governance, and compliance frameworks in AI integrations.
- Bachelor's or Master's degree in Computer Science, Engineering, or related discipline.
- Opportunity to shape enterprise-wide AI adoption strategies.
- Work with leading-edge AI and integration technologies.
- Collaborative environment with a focus on innovation and scalability.
- Competitive compensation, growth, and professional development opportunities.
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