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As an AI Prototyper & AIOps Engineer, you will rapidly test ideas, build proof-of-concepts, and operationalize AI models across diverse environments. You will work across LLMs, RAG pipelines, multimodal models, forecasting systems, and cloud-native architectures. You will help define standards for model deployment, security, monitoring, and continuous improvement ensuring reliability and scalability.
Job Responsibility:
Build rapid prototypes using LLMs, RAG, embeddings, and multimodal models
Design and implement end-to-end AIOps pipelines for training and deployment
Stand up cloud infrastructure in GCP/Azure for scalable AI workloads
Integrate structured, unstructured, and telemetry-style data into models
Implement monitoring, observability, and automated evaluation systems
Collaborate with PMs, architects, and engineers to define feasibility
Produce technical documentation and contribute to delivery frameworks
Experiment with new AI techniques and translate innovation into action
Requirements:
Bachelor’s degree in CS, Engineering, or related
5+ years in ML Engineering, AIOps, or similar applied AI functions
Strong Python, Docker, Kubernetes, CI/CD, and cloud experience
Familiarity with LLMs, open-source models, vector DBs, and RAG
Strong ability to prototype quickly and work with ambiguity