Develop and deploy scalable Conversational AI solutions, including chatbots and voicebots, using LLMs and Agentic AI. Define technical architecture and manage integrations with enterprise systems, CRMs, and telephony infrastructure.
Remote AI Engineer Jobs (2,819)
Search = AI Engineer
Own and scale the agent layer and matching engine for an AI-first fundraising platform. This includes building conversational agents for investor outreach and managing the backend data pipelines.
Own the conversation layer of an AI fundraising platform, managing agents that handle replies, booking, and relationship nurture. Build broader applied-AI features including classification, extraction, and the evaluation framework to ensure quality.
Build and optimize LLM serving and inference systems to improve performance across GPU and CPU pathways. Design and scale infrastructure supporting RAG and retrieval-heavy AI workloads to resolve throughput and latency bottlenecks.
Develop and optimize ML models from scratch while collaborating with cross-functional teams to deploy them into production. Establish experimentation roadmaps and maintain reproducible pipelines to ensure optimal model performance.
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Design and deliver AI-powered agentic architecture to automate repetitive tasks within the studio pipeline. Collaborate with technical and creative teams to integrate AI tools and establish technical standards for production stability.
Design and implement AI-powered agentic architectures and automation frameworks to eliminate repetitive tasks within the studio pipeline. Collaborate with technical and creative teams to integrate AI tools into artist-facing toolsets and establish operational standards.
Design, build, and operate agentic AI systems including prompt engineering, tool integration, and evaluation harnesses. Own the full model lifecycle from shipping new AI products to monitoring quality and cost in production.
Serve as the primary technical architect for strategic global enterprise accounts, designing complex AI engagements and data pipelines. Lead technical discovery and scoping for AI services including model evaluation, red teaming, and data strategy to ensure robust and ethical AI assets.
The role involves developing and implementing AI solutions specifically tailored for legal applications. The engineer will likely bridge the gap between legal requirements and technical AI execution.
Develop and maintain AI-powered agentic features, including a CLI, MCP server, and unified chat experience for a neo-broker platform. Lead technical conversations and contribute to architecture decisions to ensure scalable foundations for AI product experiences.
Senior Software Engineer (AI Platform) (m/f/d)
auxmoney GmbH
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Full Time
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2 Weeks Ago
auxmoney GmbH
Design, build, and operate scalable backend services and agentic workflows to power AI-enabled features. Collaborate with product managers to turn AI opportunities into reliable production-grade services while mentoring other engineers.
Own the end-to-end evaluation framework for agentic products, including golden datasets and LLM-as-judge pipelines. Build and extend agentic systems by developing new tools, sub-agents, and prompt iterations to improve production reliability.
Drive AI initiatives from design and architecture to rollout and operation, focusing on scalable production-grade services. Collaborate with product stakeholders to implement agentic workflows and maintain high engineering standards through code reviews and mentoring.
Deploy and maintain AI tools, agents, and hosting environments while managing broader cloud infrastructure on AWS and GCP. The role involves a split between AI building and traditional IT infrastructure support, including CI/CD pipeline maintenance and stakeholder management.
Build and evolve a core AI tutoring system focusing on prompt architectures, agentic workflows, and real-time adaptive behaviors. Collaborate cross-functionally to translate pedagogical goals into scalable technical solutions and productionize novel model interactions.
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Senior AI Engineer | GCP, Vertex AI, Gemini & Python | 100% Remoto (España)
The White Team
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Full Time
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2 Weeks Ago
The White Team
Design and implement AI/ML solutions and Agentic AI architectures using Vertex AI and Gemini Enterprise on GCP. Manage data platforms, automate infrastructure with Terraform, and maintain MLOps pipelines in Kubernetes environments.
Senior Go Engineer - AI Platform Backend
Yonder Media Mobile
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Full Time
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2 Weeks Ago
Yonder Media Mobile
Design and build the orchestration backend in Go, focusing on task routing, device registry, and real-time connectivity. Own the PostgreSQL schema and maintain the Django admin panel for operational configuration.
![Smart Working Solutions is hiring for remote Senior Full Stack AI Engineer (Remote, Contractual) [AS282]](/assets/08150176-369d-44db-a4a7-778571334971.png){kind=small}
Senior Full Stack AI Engineer (Remote, Contractual) [AS282]
Smart Working Solutions
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Full Time
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2 Weeks Ago
Smart Working Solutions
The role involves designing and delivering end-to-end AI-powered features and system architecture across the full stack. You will translate ambiguous stakeholder needs into production-ready solutions while scaling an existing Python-based application.
Lead the design and implementation of a production-grade agentic layer to enable AI agents to offer and fulfill refund solutions. This includes building RAG pipelines, MCP servers, and ensuring compliant AI outputs through guardrails and evaluation frameworks.
Own and drive the quality, reliability, and evolution of production AI systems, including the delivery of major AI features. Design and orchestrate agentic, tool-using AI workflows and manage prompt engineering and experimentation pipelines.
The role involves building and shipping end-to-end AI features, turning raw model outputs into reliable product behaviors. Responsibilities include designing agent workflows, optimizing for latency and cost, and developing evaluation frameworks.
The role involves building and shipping end-to-end AI features, from designing prompts and agent workflows to ensuring production reliability. You will be responsible for turning raw model outputs into structured behaviors and optimizing for latency and cost.
The role involves building and shipping end-to-end AI features, from designing prompts and agent workflows to ensuring production reliability. You will be responsible for turning raw model outputs into structured behaviors and optimizing for latency and cost.
The role involves building and shipping end-to-end AI features by turning model capabilities into reliable product behaviors. Responsibilities include designing agent workflows, optimizing for latency and cost, and debugging the full stack from model to UX.
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The role involves building and shipping end-to-end AI features, turning raw model outputs into reliable product behaviors. You will design prompts, tools, and agent workflows while optimizing for latency, cost, and production reliability.
The role involves building and shipping end-to-end AI features, transforming raw model outputs into reliable product behaviors. You will design agent workflows, optimize for latency and cost, and develop evaluation frameworks to measure real-world performance.
Own the inference and orchestration layer to build production systems that power AI interactions. Focus on designing stable APIs, optimizing latency, and managing production concerns like monitoring and incident response.
Design and operate the inference and orchestration layer to power AI interactions across mobile and desktop clients. Focus on optimizing latency, throughput, and reliability for production AI-powered features.
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