Own the inference and orchestration layer to build production systems that turn AI model capabilities into stable APIs. Focus on optimizing latency, throughput, and reliability for AI-powered features across mobile and desktop clients.
Remote AI Engineer Jobs (2,818)
Search = AI Engineer
Own the inference and orchestration layer to build production systems that turn AI model capabilities into stable APIs. Focus on optimizing latency, throughput, and reliability for AI-powered features across mobile and desktop clients.
Build the product layer for AI-native workflows, focusing on agent design, tool integration, and system reliability. Develop end-to-end features across the frontend and backend to create proactive, goal-driven AI assistants.
Design and operate the inference and orchestration layer that powers AI interactions, focusing on latency, reliability, and cost. Build production systems to turn model capabilities into stable APIs for mobile and desktop clients.
Build and deploy production-grade AI-native product features and agent workflows that handle multi-step reasoning and tool use. Focus on improving system reliability, reducing latency, and creating proactive, goal-driven user experiences.
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Build the product layer for AI-native workflows, focusing on agent design, failure recovery, and real-time interactions. Collaborate with ML and backend teams to ship end-to-end features that move beyond simple chat into goal-driven workflows.
Build the product layer for AI-native workflows, focusing on agent design, tool integration, and system reliability. Develop end-to-end features across the frontend and backend to create proactive, goal-driven AI assistants.
Build and deploy production-grade AI-native product features and agent workflows that handle multi-step reasoning and tool use. Focus on improving system reliability, reducing latency, and creating proactive AI interactions for everyday users.
Build the product layer for AI-native workflows, focusing on agent design, tool integration, and system reliability. Develop end-to-end features across the frontend and backend to create proactive, goal-driven AI assistants.
Design and implement a scalable agentic framework and centralized AI platform to support organization-wide AI initiatives. Collaborate with cross-functional teams to integrate AI agents into internal tools and customer-facing applications while ensuring security and scalability.
Lead the technical direction and design of production-grade AI systems and multi-model pipelines for a healthcare platform. Establish AI engineering standards, observability tools, and safety guardrails to ensure scalable and reliable solutions.
Design and implement end-to-end AI-powered products, including frontend interfaces, backend services, and AI/ML integrations. Collaborate with cross-functional teams to ship scalable features that optimize real estate asset management and leasing.
Design and implement AI-driven document processing and search solutions using Azure AI Search and RAG architectures. Manage containerized deployments via AKS and optimize vector search and query orchestration for intelligent knowledge retrieval.
Lead the transition of the card operations AI agent from internal pilot to a production-grade system. Expand agent capabilities into accounting automation and policy enablement while ensuring reliability, safety, and cost-efficiency.
Lead the design, development, and deployment of advanced AI systems and scalable LLM-driven applications. Act as a technical authority for clients while mentoring peers and supporting presales activities.
Design and develop Agentic AI solutions to automate complex enrollment and benefits administration exceptions. Modernize rule engines by combining deterministic business rules with probabilistic AI reasoning and implementing scalable MLOps pipelines.
AI Engineer I
Welbehealth Non Sponsored Board
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Full Time
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3 Weeks Ago
Welbehealth Non Sponsored Board
Support the design, development, and implementation of AI-powered solutions and RAG systems to improve participant care and operational efficiency. Collaborate with senior engineers to prototype, test, and deploy enterprise AI applications within a healthcare environment.
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Design and build the foundational internal AI platform and shared capabilities to improve operational efficiency across GTM and G&A functions. Establish engineering standards, architectural patterns, and integration layers for business tools like Salesforce and Databricks.
Lead the design and implementation of high-performance data movement pipelines and storage architectures for AI inference. Optimize I/O paths between GPU memory and distributed storage to enable ultra-low-latency AI workloads.
Comcast Cybersecurity: Cyber Security Engineer – AI & Agentic Platforms
Comcast
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Full Time
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3 Weeks Ago
Comcast
Develop and maintain the Premonition platform for managing and deploying agentic pipelines to power global cybersecurity operations. Optimize the high-performance data layer and collaborate with security teams to translate workflows into automated, observable systems.
Customer Solution Engineer - AI Native/Consumption Quote to Cash
Zuora
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Full Time
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3 Weeks Ago
Zuora
Drive technical wins in enterprise sales cycles by designing and building complex quote-to-cash and AI-native monetization solutions. Act as a technical SME to ensure account health, guide architecture best practices, and support customer adoption.
Translate business requirements into production-ready AI solutions and workflows using tools like Claude, ChatGPT, and n8n. Develop and govern a centralized enterprise AI platform, including RAG solutions and AI agents, while ensuring security and data privacy.
Translate business requirements into productive AI solutions and workflows using tools like n8n, Claude, and ChatGPT. Develop the company-wide AI platform, including data integration, RAG applications, and governance frameworks.
Design, build, and deploy production-grade ML and LLM-based systems for enterprise clients. Own the end-to-end technical delivery from architecture and prototyping to monitoring and mentoring junior engineers.
Design and implement AI solution architectures, including APIs and data extraction/transformation pipelines using Python. Act as a technical interlocutor for clients and deploy scalable solutions in the cloud following clean architecture patterns.
Design and develop AI-enabled features and agentic workflows for web-based government applications using LLMs and GenAI. Implement RAG pipelines and establish LLM observability and responsible AI guardrails.
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Architect, scale, and optimize scientific codebases to power Large Quantitative Models for drug and materials discovery. Transition high-impact research prototypes into robust, production-grade software and orchestrate distributed training pipelines on GPU infrastructure.
Senior Applied Artificial Intelligence (AI) Engineer (Insurance Domain Experience)
Milliman
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Full Time
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3 Weeks Ago
Milliman
The role focuses on bridging insurance domain expertise with AI engineering to redesign workflows and implement AI-enabled transformation solutions. Responsibilities include leading client engagements, mapping current-state insurance processes, and co-designing practical AI prototypes and roadmaps.
Design and deliver production-ready AI applications focusing on RAG pipelines, agentic workflows, and document ingestion. Provide technical leadership and mentorship to engineers while collaborating cross-functionally to align AI capabilities with business objectives.
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