Top Remote AI Engineer Jobs

As a Founding AI/Data Engineer, you'll design and build AI-driven products, collaborate across teams, and ensure system reliability while enhancing user experiences.

Design and implement full-stack applications for GenAI, build developer tooling, collaborate with product teams, and enhance AI agent delivery.

Design and implement full-stack applications and AI agents to enable rapid development and deployment of AI solutions in critical industries. Mentor engineers and take ownership of projects while applying secure SDLC practices and collaborating with cross-functional teams.

Own and operate the realtime voice stack and call-data platform end-to-end: telephony/WebRTC integration, streaming STT/TTS, realtime voice agents, call-to-transcript pipelines, data warehousing, analytics, and dashboards. Build AI-native workflows, RAG/search, human-in-the-loop flows, and optimize performance, latency, and cost. Mentor teammates and collaborate across product and subject-matter experts.

Build and maintain full-stack product and AI systems: React/React Native frontends, Node.js services, LLM-powered features (agents, RAG), integrations, monitoring, and scalable automation. Ship production features, ensure reliability, and mentor teammates.

Design and implement an MLIR-based AI compiler for GPU inference: develop graph representations and dialects, optimize performance and memory, define APIs, generate kernels, and collaborate with framework and hardware teams to enable new model patterns and GPU features.

Develop and support Rescale's HPC platform, integrate AI into CAE workflows, solve customer HPC/AI problems, build AI software, collaborate with engineering teams, and engage directly with customers.

Design, deploy, secure, and maintain enterprise Windows endpoints (Windows 10/11) supporting AI-enabled desktop capabilities. Administer Intune/Endpoint Manager, implement STIG-compliant baselines, configure Conditional Access and Zero Trust controls, automate provisioning with Autopilot and PowerShell, integrate endpoint telemetry with security tools, and support audits and compliance in government cloud environments.

Design, build, deploy, and operate AI/ML capabilities in AWS GovCloud using FedRAMP-authorized services. Responsibilities include data preparation, model development, evaluation, deployment, monitoring, RAG implementations, embedding/vector search integration, Python development of production services, containerized deployments, CI/CD, and collaboration with engineering and cybersecurity teams to meet mission and compliance requirements.

Design and optimize AI communication middleware for distributed multi-node, multi-GPU training. Implement C/C++ performance-critical features, improve GPU communication paths, profile and tune frameworks (PyTorch, TensorFlow, JAX, DeepSpeed), develop benchmarks, contribute upstream, and collaborate with kernel, driver, switch, and systems teams to validate and deploy high-performance networking for AI/HPC.

Senior technical lead for APAC partners driving partner enablement, co-selling, and technical leadership around Talkdesk CCaaS/CXA. Responsibilities include advanced demonstrations, solution design, ecosystem integrations, Agentic AI implementations, partner competency development, and regional representation with ~35-70% travel.

Define and build Fuse's inference-serving architecture and stack, including request routing, batching, scheduling, and autoscaling for latency-sensitive workloads. Own model-level optimizations (quantisation, distillation, speculative decoding), translate performance SLAs into capacity plans, and integrate low-level GPU/CUDA performance work with serving infrastructure. Set benchmarks, tooling, and act as technical owner of inference performance and reliability.

Lead operations for large-scale AI infrastructure: manage NVIDIA GPU and high-performance networking environments, troubleshoot Linux/Kubernetes/storage/hardware issues, drive incident response and root cause analysis, improve observability and automation, mentor engineers, and collaborate with engineering and datacenter teams to ensure platform reliability and scalability.

Lead architect and hands-on builder for AI solutions: evaluate feasibility and data readiness, translate business problems into technical and algorithmic requirements, design high-level architectures and prototypes, drive PoC to production handover, set MLOps/API standards, mentor team, and align North American implementations with European enterprise governance.

Lead design and development of enterprise software solutions using Java and Cursor AI. Provide technical leadership, mentor engineers, define architecture and roadmaps, implement cloud-native, microservices, CI/CD and infrastructure-as-code practices, and collaborate across product and engineering teams to deliver performant, secure systems.

Lead the AI engineering org for a YC-experienced startup: drive 0->1 product development, design full-stack architectures, partner with customers and product, mentor engineers, and establish scalable production AI systems and technical strategy.

Build customer-facing AI products and agentic automation, modernize core architecture, improve observability and CI, ship full‑stack features (TS/Node/NestJS/React/Postgres), mentor engineers, and influence engineering practices across the organization.

Design, develop, and upstream-enable AI/HPC communication middleware (MPI/SHMEM, NCCL/RCCL). Integrate middleware with transports (libfabric/UCX/verbs), optimize performance, collaborate across kernel/driver and switch teams, analyze performance traces, reproduce and fix customer issues, and contribute to open-source projects.

Develop and optimize AI/HPC communication middleware (MPI/SHMEM, CCL/NCCL/RCCL) over Cornelis interconnects; integrate with transports (libfabric/OFI, UCX), contribute upstream open-source, collaborate across kernel/driver and switch teams, and analyze performance traces to reproduce and fix customer issues.

Build and maintain backend services and infrastructure for ML and generative AI features. Develop scalable, resilient, high-performance Python services (async frameworks, streaming), deploy to Kubernetes, integrate RAG and LLM orchestration, instrument LLM observability, and collaborate cross-functionally to deliver production-ready AI products.

Lead development and adoption of AI-driven and traditional test automation, maintain UI automation frameworks, own performance/load testing strategy, align testing to architecture and risk, mentor QA engineers, and collaborate with product and engineering to improve quality and testing efficiency.

Lead architecture and implementation of agentic AI systems powering Zuma's platform. Rebuild onboarding and integration frameworks, implement analytics and observability for LLM performance, translate product needs into technical solutions, mentor engineers, establish engineering standards, and work directly with customers to enable scalable, production-grade AI experiences.

Lead end-to-end development and production deployment of agentic AI systems and full-stack products. Architect integrations with property management systems, improve reliability and observability, define engineering standards, and partner with product and operations to ship scalable AI agents across voice, text, and email.

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

The Software Engineer will develop backend systems for an AI Energy Agent, including data integration, microservices, and scalable architecture, focusing on performance and reliability.