AI/ML Integration Engineer

Responsibility •Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools. •Ensure seamless deployment and integration between cloud/prem environments (AWS). •Integrate AI models into production environments using containerized platforms such as OpenShift. • Implement and maintain network security protocols to safeguard AI systems and data pipelines. •Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions. •Monitor and optimize system performance, reliability, and scalability. •Support CI/CD processes and infrastructure for AI model deployment and updates. Required Qualifications • Bachelor’s degree in Computer Science, Engineering, or a related field. • 2+ years of experience in Machine Learning engineering or AI system integration. • Bash and Unix/Linux command-line toolkit is a must-have. • Hands-on experience with OpenShift, Docker, Kubernetes. • Knowledge of cloud platforms (e.g. AWS) is a must-have. • Exposure to data and network security and compliance in AI systems. • Knowledge of API integration and microservices architecture. • Proficiency in Python used both for automation and ML-related tasks • Knowledge of Workflow Orchestrator, such as Ctrl-M • Good knowledge of Logging and Monitoring tools, such as Splunk and Geneos. • Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry. • Understanding of Generative AI (e.g. prompt engineering, RAG pipelines) and Agentic AI concepts. Interested - Apply here or share your cv at ankita.kesari@tangspac.com