Top Remote AI Engineer Jobs

Build production-grade AI agents and RAG pipelines that integrate with internal tools (BookStack, Slack, Asana, Gmail). Create REST APIs, ingestion pipelines, and function-calling workflows; monitor and iterate on agent performance while collaborating with backend (.NET) and frontend (Angular) teams.

Build AI-driven developer tools: coding assistants, knowledge retrieval, workflow automation, and LLM-powered apps for code generation, understanding, and test automation. Collaborate with engineering teams to identify pain points, ship solutions, and experiment with prompt engineering, RAG, and AI agents.

Early-career software engineer in a fixed-term accelerator contributing to backend/full-stack feature development, testing, CI/CD, and deployments. Collaborate on API and system design, integrate and deploy AI/LLM capabilities (LLM APIs, RAG, embeddings, agents), build datasets/benchmarks, monitor performance, debug issues, and produce technical documentation.

Build internal AI developer productivity tools (coding assistants, retrieval systems, workflow automation). Develop LLM-powered apps for code generation, understanding, and test automation. Integrate AI across the SDLC, embed with teams to remove friction, experiment with prompt engineering, RAG, and AI agents, and evaluate emerging AI technologies.

Lead and deliver an enterprise AI platform and agent factory: design architecture, build cost-effective model infrastructure, harden security/SSO/IAM, enable developer adoption, and build agent workflows across the PDLC (ideation, development, deployment). Mentor engineers, steer delivery partners, and remain hands-on implementing agents, RAG pipelines, integrations, and observability to drive measurable productivity gains.

Lead AI security strategy and guardrails, design and review AI gateways and tooling, scale InfoSec review processes, reduce AI-driven security noise, drive remediation and investigations, and mentor security and platform engineers.

Design and deploy production-grade LLM-powered systems (RAG, agents, pipelines). Integrate AI across products, fine-tune and evaluate models, define prompt/modeling best practices, monitor model performance, and mentor engineers.

Build a cross-platform endpoint agent to detect and attribute AI-generated code at the line level, design pipelines to capture/classify/store developer and agent activity, work with Git internals, integrate with coding agents, and ensure reliable, invisible production deployments across macOS, Linux, and Windows.

As a Distinguished Engineer, you will lead technical innovation in AI-driven marketing systems, mentor talent, and guide architecture design. You will collaborate across teams to optimize banking solutions and influence future technology at Capital One.

Lead design and implementation of production agentic AI systems that integrate LLMs with Teak's platform APIs. Build RAG pipelines, MCP/tool integrations, evaluation frameworks, and AI infrastructure on cloud (AWS/GCP/Azure). Contribute backend services in Python, ensure compliance and safety, and operate systems in production including observability and on-call duties.

As a Staff Backend AI Engineer, you will design and operate backend AI systems for Arbiter's care orchestration platform, ensuring reliability, low latency, and scalability while collaborating across teams and mentoring junior engineers.

Lead design, deployment, and monitoring of LLM-based AI solutions. Build end-to-end generative AI applications, fine-tune models, integrate LLM APIs into products, ensure post-deployment performance, and collaborate cross-functionally within an Agile environment to drive measurable business impact in healthcare.

The Senior AI Engineer will design and maintain customer-facing AI tools by building APIs, optimizing workflows, and conducting experiments with generative AI models, ensuring system reliability and integration with production systems.

Design, build, and ship AI-powered observability features using LLMs and agentic workflows. Rapidly prototype, iterate with real users, integrate AI into alerting, runbooks, and developer workflows, and ensure solutions are scalable, maintainable, and production-ready while collaborating cross-functionally.

Design, develop, and maintain scalable CPQ solutions on Salesforce. Implement Apex and Lightning components, optimize existing systems, and mentor junior developers.

Design, build, and deploy production-grade ML and AI solutions for behavioral health. Architect end-to-end MLOps pipelines, optimize and monitor models in production, evaluate emerging AI trends, collaborate cross-functionally, and provide technical leadership and mentorship to engineering teams while ensuring responsible, scalable, and secure AI deployments.

Lead cloud migrations for voice contact center solutions, design AI/ML capabilities, improve automation and governance, and ensure production readiness while collaborating with cross-functional teams.

Lead design, development, and production deployment of AI/ML solutions and conversational chatbot platforms. Own end-to-end implementation, MLOps/CI-CD, containerized deployments, solution architecture, security and governance, mentor engineers, and collaborate with product, enterprise architecture, and vendors to deliver scalable, monitored AI systems.

Lead technical design and delivery of production AI/ML and GenAI solutions (RAG, LLMs, agents). Build, tune, deploy, and monitor models and APIs, own MLOps practices, operate cloud AI workloads, ensure software quality and responsible AI, and partner with cross-functional stakeholders while mentoring engineers.

Design, build, and operate Jellyfish's Databricks Lakehouse and data/AI platform. Build ingestion, transformation, and delivery pipelines; govern data with Unity Catalog; enable BI, agentic analytics, metadata, lineage, and observability. Provide technical leadership, set architecture and standards, mentor peers, and collaborate with cross-functional stakeholders to make Databricks the foundation for analytics and AI.

Own and improve the AI Social render pipeline and agent loops that generate on-brand Instagram carousels and reels. Build prompts, structured outputs, tool-calling, and media composition to ship high-quality generative image, video, voice, and music products in collaboration with product, design, and content strategy.

Build and operate Coinbase's LLM and agent platform: unified model gateway, AI Hub, secure microVM agent runtime, knowledge base integrations, AI FinOps, observability and evaluation tooling, and production-grade agent deployments with teams across the company.

Lead design, build, and operation of production AI systems and inference stacks (vLLM) across AI Factory platforms. Implement RAG, MLOps, storage/networking, Kubernetes/containers, monitoring, security, and on-call incident response. Mentor engineers, engage clients, author runbooks, and contribute reusable patterns and tooling.

The AI Engineer will develop scalable AI systems, automate workflows, and collaborate with business teams to enhance operational efficiency across OpenSesame.

The AI Engineer will design, develop, and deploy AI-powered systems, improve operations with intelligent workflows, and collaborate on high-leverage AI opportunities.