Architect and deploy autonomous AI agents and strict-source-following RAG systems to power privacy-first product capabilities. Build scalable backend services and rigorous evaluation pipelines to ensure reliability, compliance, and performance.
Remote AI Engineer Jobs (2,146)
Search = AI Engineer
Artificial Intelligence (AI) Engineer
General Dynamics Mission Systems, Inc
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Full Time
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Yesterday
General Dynamics Mission Systems, Inc
Build and deploy production-grade AI services, including agentic workflows and RAG pipelines, for a large-scale defense enterprise. Design secure API interfaces and containerized deployment pipelines to integrate AI services with internal enterprise platforms.
Senior, AI Engineer - AA, Remote: Colombia - Costa Rica, Fulltime, Digital Product Development
Gorilla Logic, LLC
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Full Time
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Yesterday
Gorilla Logic, LLC
Design, build, and deploy production-grade generative AI solutions and RAG pipelines for enterprise clients. Develop agentic systems and maintain evaluation frameworks to ensure model performance and safety.
Design and maintain agentic AI workflows and generative media pipelines to accelerate studio production. Build internal AI tools and dashboards that enable non-technical teams to access AI workflows independently.
Build and maintain the master data enrichment pipeline, focusing on classification and entity resolution workflows using deterministic logic and LLMs. Develop evaluation harnesses and regression suites to ensure high data quality and pipeline reliability.
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Configuration / Release Engineer — AI Reliability Engineering
General Dynamics Mission Systems, Inc
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Full Time
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Yesterday
General Dynamics Mission Systems, Inc
Establish and maintain configuration baselines for AI artifacts including code, models, and prompt libraries. Manage the release process and change control to ensure audit compliance and reliable rollback capabilities across environments.
The role focuses on accelerating AI adoption within the marketing team by building and optimizing AI-powered tools and agentic workflows. Responsibilities include managing MCP connectors, establishing AI governance frameworks, and leading team enablement through office hours.
Lead the design and build-out of the AI Context Layer, including knowledge graphs and RAG engines, to provide AI agents with high-quality data. Drive the technical roadmap, define developer interfaces, and establish governance and security standards for data access.
Lead and mentor a team of three to eight software engineers, focusing on their professional growth and performance. Drive the delivery of value to customers by managing timelines, priorities, and handling customer escalations.
Senior Software Engineer, AI Platform & Agents
Coalition, Inc.
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Full Time
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Yesterday
Coalition, Inc.
Lead the development of an internal AI platform and orchestration components to accelerate the deployment of AI Agents and RAG pipelines. Build core infrastructure, SDKs, and APIs that enable engineering teams to integrate LLM capabilities into production-grade applications.
Senior Software Engineer, AI Platform & Agents
Coalition, Inc.
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Full Time
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Yesterday
Coalition, Inc.
Lead the development of an internal AI platform and orchestration components to accelerate the deployment of AI Agents and RAG pipelines. Build scalable SDKs and APIs that bridge the gap between LLM capabilities and production-grade applications.
Develop and deploy production-grade AI solutions spanning classical ML, deep learning, and Generative AI. Establish robust MLOps pipelines for training, evaluation, monitoring, and scaling multi-customer deployments.
Design and maintain scalable backend services, APIs, and event-driven microservices using Java, Python, and Kafka. Build and integrate AI/ML-powered features and data processing pipelines while ensuring production readiness through CI/CD and monitoring.
Develop and ship AI product features and agent infrastructure using a full-stack approach with Golang and React/TypeScript. Own the user experience in Canvas and maintain software reliability through on-call rotations and incident investigation.
API / Integration Engineer - AI Reliability Engineering
General Dynamics Mission Systems, Inc
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Full Time
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Yesterday
General Dynamics Mission Systems, Inc
Design and build connections between AI platforms and enterprise systems such as ERP, CRM, and legacy databases. Develop RESTful and event-driven APIs while ensuring data flow reliability, security, and compliance.
Artificial Intelligence (AI) Engineer
General Dynamics Mission Systems, Inc
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Full Time
·
Yesterday
General Dynamics Mission Systems, Inc
Build and deploy production-grade AI services, including agentic workflows, RAG pipelines, and LLM-integrated applications. Design secure API interfaces and containerized deployment pipelines to integrate AI services with enterprise data platforms.
Lead the design and implementation of advanced AI/ML systems, pipelines, and model-serving architectures for enterprise workloads. Mentor junior engineers and collaborate with stakeholders to drive technical decision-making and AI transformation strategies.
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Design and build scalable backend platform services to power AI-enabled customer data products and real-time configuration workflows. Collaborate cross-functionally to implement AI assistants, orchestration flows, and high-traffic APIs using modern Java frameworks.
Agentic AI Engineer
General Dynamics Information Technology
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Full Time
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Yesterday
General Dynamics Information Technology
Design, develop, and deploy production-grade multi-agent AI solutions and pipelines to enhance organizational productivity and automation. Collaborate with cross-functional teams to integrate agentic AI services into enterprise systems while maintaining AIOps practices.
Drive the architecture and technical strategy for Redis Search and Vector capabilities to power AI workloads at global scale. Lead cross-team initiatives and translate industry trends into production-ready platform capabilities.
Lead the design and implementation of advanced AI/ML systems, pipelines, and model-serving architectures for enterprise workloads. Mentor junior engineers and collaborate with stakeholders to drive technical decision-making and AI transformation.
Design, implement, and deploy end-to-end production AI/ML systems including data pipelines and training workflows. Collaborate with cross-functional teams to integrate AI agents into enterprise operations and maintain system reliability and scalability.
Design and implement scalable AI-driven applications, including front-end interfaces and backend services with AI capabilities. Develop RESTful APIs and optimize machine learning pipelines using quantized models for legacy hardware.
Design and implement intelligent conversational agents using agent-based architectures and LLMs. Integrate these agents with corporate systems, REST APIs, and cloud environments like GCP Vertex AI while ensuring scalability and quality.
System Operations Engineer - AI Trainer - Freelance - 8-20hrs/week - Remote
10x Team
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Full Time
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Yesterday
10x Team
Review and refine AI-generated content and workflows related to system operations and automation. Develop real-world use cases and provide actionable feedback to improve AI reasoning in operational scenarios.
System Operations Engineer - AI Trainer - Freelance - 8-20hrs/week - Remote
10x Team
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Full Time
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Yesterday
10x Team
Review and refine AI-generated content and workflows related to system operations and automation. Develop real-world use cases and risk assessments to improve how AI models reason about operational challenges.
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Design, prototype, and deploy AI-driven solutions using LLMs and agentic workflows to improve operational efficiency. Integrate various enterprise platforms and collaborate with stakeholders to identify and implement high-impact AI use cases.
Lead end-to-end AI tasks and guide the engineering team's architecture to improve scalability and stability. Collaborate with product teams to translate business needs into efficient, maintainable, and creative technical solutions.
Design and implement AI solutions using RAG and agentic architectures to solve complex business problems. Manage data ingestion pipelines and deploy models using MLOps and serverless architectures.
Design and deploy production-ready AI agents for strategic customers, integrating them with CRMs and telephony systems. Bridge the gap between Sales and Engineering by converting pilots into scalable platform capabilities and providing technical validation.
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