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ABOUT THE ROLE We are seeking a hands-on AI Applications Developer to design, build, integrate, and support enterprise AI-enabled applications, copilots, document intelligence solutions, knowledge search experiences,…
Build and deploy AI-powered healthcare solutions using LLMs, RAG, and Azure services to automate document processing and enhance clinical insights for payors and providers.
Build and maintain a secure AI platform for law-enforcement investigations, integrating LLMs, RAG, and agentic workflows with backend services and frontend interfaces.
Build and refine ML/LLM-based systems to automate customer support and troubleshooting at Snowflake, using Python/Java services and Kubernetes.
Build and deploy production-grade generative AI applications using Python, LLMs, and libraries like Transformers, LangChain, and Hugging Face.
Build and deploy ML models for retail forecasting, personalization, and computer vision/LLM use cases using Python, Spark, and cloud platforms.
Build and deploy computer vision and generative AI models for retail applications like visual search, personalized recommendations, and fraud detection using PyTorch, diffusion models, and multimodal systems.
Build and lead Mercor’s code-search systems: hybrid retrieval (dense embeddings + BM25) that routes coding tasks to the right models and turns natural-language questions into precise code retrieval at scale.
Build and deploy AI/ML models, NLP, and LLM solutions to extract insights from unstructured data and support business decisions using Python, cloud platforms, and vector databases.
Lead the roadmap for Splunk’s AI Foundations platform, defining domain-specific models, agentic protocols, and orchestration tools to power enterprise-grade AI workflows for global customers.
Lead the design and implementation of enterprise AI and data platforms on GCP, building scalable, secure cloud-native solutions with Vertex AI, BigQuery, and automation while mentoring engineers and enforcing governance.
Build and maintain AI-enabled full-stack applications for memory and storage manufacturing workflows, integrating custom agents, RAG systems, and MCP-based tooling.
Design and deliver enterprise-grade AI systems using LLMs, RAG, agentic workflows, and cloud-native platforms while ensuring security, compliance, and scalability for Nordic customers.
Builds backend systems in Java/Python to integrate AI/ML models (LLMs, embeddings) into scalable, production-ready agentic AI workflows for ING’s digital platforms, ensuring reliability, security, and observability while collaborating with data scientists and product teams.
Build and deploy autonomous agentic AI systems using RAG pipelines, vector databases, and multi-agent architectures on GCP to automate workflows and replace manual processes.
Leads a tiger team to modernize AI/ML platforms, integrating LLMs (RAG, embeddings) and automating data pipelines for customer identity resolution, while mentoring teams on next-gen AI development and .NET/React-based infrastructure.
Designs enterprise AI solutions on Microsoft’s stack, setting standards and guiding teams to build secure, scalable GenAI apps using Azure AI, Copilot Studio, and modern frameworks.
Mid-level AI developer building and integrating locally hosted LLMs and ML models into classified government systems, focusing on secure, air-gapped environments and production-grade AI features.
Build and optimize AI-ready data pipelines, vector stores, and retrieval systems using Airflow, Elasticsearch, and Python to power large-scale AI models and RAG applications.
Lead AI engineering for classified systems: design, deploy, and secure LLMs and ML models in air-gapped environments while aligning with government accreditation and responsible-AI practices.
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