Top Remote AI Engineer Jobs

Design, build, and scale production-grade, stateful AI agent systems integrated into core product flows. Implement LLMOps, observability, containerized CI/CD deployments, RAG/vector DBs, evaluation pipelines, performance/cost optimizations, and mentor junior engineers.

The Senior AI Engineer will develop and deploy multi-agent systems, automate workflows, integrate enterprise systems, and mentor junior engineers while ensuring quality and security compliance.

Lead AI technical strategy, architect AI systems, set safety standards, mentor engineers, and evaluate AI models at Midi Health, a healthcare-focused company.

You will design and build LLM-powered features, integrate AI capabilities into workflows, and contribute to internal practices at a healthcare-focused company.

Join the AI Transformation team to co-develop and productionize the Elixir AI platform: implement runtimes, retrieval/memory, multi-model routing, observability, secure multi-tenant features, event-driven agents, and productize FDE-built solutions while partnering with stakeholders and shipping high-quality production software.

The Staff AI Engineer will build the AI platform, apply LLMs for intelligent feature development, and ensure system scalability and security while optimizing performance.

The Senior AI Engineer will design and implement scalable AI platform services, integrate large language models, and optimize AI capabilities within ClickUp's product, collaborating across teams for innovation.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

Lead and mentor a team of 4-8 engineers to build and evolve AI developer tools for local and cloud GPU workflows. Define roadmaps with product partners, manage cross-team dependencies, drive technical execution, improve engineering efficiency via tools and automation, and ensure security and compliance.

Design, build, and operate production multi-agent AI systems and automation for Marketing Operations. Integrate LLMs with business data (BigQuery, CRMs, Slack), build MCP servers, APIs, and scalable serverless/containerized services, implement observability and governance, and partner with GTM teams to deliver measurable automation and self-service workflows.

The Senior Software Engineer will develop AI-powered workflows and internal tools, ensuring integration with sales and operational systems, while collaborating with various teams to enhance efficiency and automation.

Design, build, and operate production-grade AI and automation systems for GTM teams. Implement multi-agent architectures, integrate LLM APIs and marketing/CRM platforms, maintain CI/CD and reliability, enable stakeholders with docs and playbooks, and measure business impact through routing, analytics, and human-in-the-loop orchestration.

The Senior AI Engineer will design and implement AI-driven product features, lead architecture reviews, and manage projects from inception to production, using tools like TypeScript and AWS.

The Staff AI Engineer will lead AI product initiatives, design technical architecture for AI systems, and enhance engineering practices with AI integration while collaborating with product and CTO teams.

Design and build multi-agent AI systems (memory, tools, feedback), orchestrate LLMs and RAG, implement REST APIs and full-stack (Node.js/Next.js), optimize databases and cloud infra, integrate embeddings and video classification, lead design-to-deployment, enforce code quality and testing, and collaborate with product and design.

Design and build multi-agent AI systems and RAG pipelines, orchestrate LLMs and embeddings, develop scalable full-stack (Node.js/Next.js) APIs, optimize infra (SQL, AWS/GCP, Docker/K8s), lead technical design-to-deployment, ensure code quality, and implement video content classification and tagging for influencer marketing.

Build end-to-end AI systems from raw context to production agents: design agent surfaces, backends, APIs, integrations, and observability/evaluation frameworks; participate in client scoping and SOWs; drive tooling, review AI-generated code, and create reusable playbooks.

Lead design and implementation of the enterprise AI orchestration and retrieval platform: build MCP servers, define tool-surface and multi-agent patterns, design RAG systems and chunking, implement routing/context/window management and observability, set evaluation and safety standards, onboard product teams, and mentor engineers to raise orchestration and retrieval maturity.

The Software Architect will lead AI quality evaluation, design evaluation frameworks, create risk controls, and ensure compliance, partnering with various teams on AI systems.

Lead enterprise model-training strategy for Commercial AI products: fine-tune LLMs (QLoRA/LoRA/PEFT), train traditional ML models, design large-scale data pipelines, enforce data governance and PII handling, build reproducible experiment/training pipelines, optimize GPU/distributed training costs, and mentor teams to operationalize models into production.

Build and lead the internal AI platform: design reusable AI services, agentic systems, and orchestration; integrate Salesforce, Gong, Databricks and vector DBs; set engineering standards, monitoring, governance, and deployment practices; translate business needs into production AI solutions and present technical recommendations to senior leadership.

Build and operate DV's model layer: fine-tune and distill open-weight models, run on-prem inference infrastructure on Kubernetes, implement a model gateway routing across providers, evaluate model quality/cost/latency, manage GPU provisioning and utilization, and define tooling for model selection and production regression testing.

Design, build, and deploy production-grade ML and LLM systems (RAG, fine-tuning, embeddings, agentic workflows). Own end-to-end technical delivery, collaborate with client teams, mentor junior engineers, improve MLOps/CI/CD, and shape internal best practices and tooling for scalable AI products.

As a Lead AI/ML Engineer, you will design and implement scalable AI solutions, mentor teams, and integrate cutting-edge technologies to improve healthcare applications.

Develop and deploy machine learning solutions for autonomous vehicles, mentoring engineers and collaborating on model implementations.