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Build and maintain an internal AIOps/ML/LLM platform, including Kubernetes infrastructure, ML workflows, and production deployment for cybersecurity use cases.
Build and productionize generative AI models and LLM-driven applications using PyTorch, RAG pipelines, and vector databases, while engineering robust MLOps and data pipelines in Python.
Principal CX Architect designs and delivers AI-native contact center solutions using Amazon Connect, Bedrock, and Lex, leading a team to build scalable conversational AI, routing, and analytics while ensuring production-grade reliability and security.
Lead a team of AI/ML scientists and engineers to build agentic workflows and reasoning engines for Pipedrive’s AI-native CRM, shipping production-grade models that drive customer value from structured and unstructured data.
Build and deploy AI-powered NLP/LLM features for a SaaS quality-management platform used by global contact centers, working with Python, Hugging Face, and AWS.
Lead AI Engineer designs and delivers enterprise-grade AI solutions, including LLM apps, RAG systems, and AI agents, while setting engineering standards and mentoring teams.
Lead the design and implementation of scalable GenAI, LLM, and AI-agent architectures, including RAG and MLOps/LLMOps pipelines, to deliver enterprise solutions and accelerate client adoption.
Build and deploy production-grade GenAI applications using LLMs, RAG, and agentic workflows integrated with Snowflake, focusing on reliability, observability, and semantic alignment.
Job Description AI Singapore (AISG) is a national AI programme launched by the National Research Foundation (NRF) to anchor deep national capabilities in Artificial Intelligence (AI). The programme office is hosted by…
Build and deploy AI agents and GenAI solutions using Azure AI Foundry, OpenAI, and LangChain, focusing on RAG pipelines, copilots, and agentic workflows.
Design and implement scalable cloud data architectures, lead Data Lakehouse development, and build ETL/ELT pipelines using Python, SQL, and Spark for a government-linked AI platform.
Design and build scalable cloud-native data pipelines and lakehouse architectures for a government housing agency, using Python, Spark, Kafka, and AWS services.
Design and build scalable cloud data pipelines and lakehouse architectures for a government project, using Python, Spark, Kafka, and AWS services.
Design and build scalable cloud-native data pipelines and lakehouse architectures, integrating AI/ML capabilities for a government data platform using Python, Spark, Kafka, and AWS services.
Design and maintain enterprise-scale AI platforms, deploying and optimizing LLMs and vision models on NVIDIA SuperPods/Cloud using Kubernetes, Docker, and CI/CD pipelines.
Design and run enterprise-scale AI platforms, deploying LLMs and vision models on NVIDIA GPU clusters, optimizing inference pipelines with Kubernetes and OpenShift, and ensuring high availability and performance.
Build and deploy AI/ML models for Saudi Aramco’s energy and sustainability projects using Python, LLMs, and cloud tools like GCP/OpenShift and Kubernetes.
Build and deploy AI/ML models, including LLMs and Generative AI, using cloud platforms and MLOps in an enterprise environment.
Build and deploy AI/ML models, including LLMs and Generative AI, using cloud platforms, Kubernetes, and MLOps for Saudi Aramco in Dhahran.
Lead the design of scalable, AI-powered data pipelines and lakehouse architectures for a global food manufacturer, optimizing cloud costs and enforcing governance across real-time streaming and ETL workflows.
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