Top Remote AI Engineer Jobs

The role involves developing cloud-native applications and AI features for data governance using Azure and Microsoft 365, focusing on security and compliance in regulated environments.

Build and operate an AWS-native data lake and AI gateway. Implement and maintain lakehouse architecture (Iceberg) using Glue, Athena, and S3; manage infrastructure as code (Terraform); run reliable data pipelines; operate LLM gateway/Bedrock; enforce security, IAM, networking, and secrets controls; partner with IT and Security.

Design, build, and deploy production ML models (time series forecasting and NLP). Perform EDA, feature engineering, model evaluation, and translate business problems into ML solutions. Maintain production model-serving pipelines and collaborate across teams to deliver scalable data-driven systems.

Transform AI prototypes into secure, scalable production systems by re-architecting code, designing cloud infrastructure (AWS/Azure), implementing CI/CD, containerizing (Docker/Kubernetes), ensuring security/compliance, building APIs, monitoring, and enabling developer productivity with infrastructure-as-code, reusable templates, and documentation.

Design and implement AI-enabled workflow orchestration, integrations, and automation pipelines across legal workflows. Build agent orchestration, vector retrieval, API/webhook integrations, monitor reliability and performance, ensure governance and compliance, and collaborate with product, legal, and operations teams to scale AI-native legal service delivery.

Design and implement AI-native workflow orchestration and automation systems for legal service delivery. Build integrations between AI platforms, CRMs, document systems, client portals, and payment systems; implement retrieval, prompt orchestration, event-driven pipelines, and observability. Monitor reliability, troubleshoot bottlenecks, support compliance and governance, and document architectures while evaluating emerging automation tools.

Design, build, and maintain AI-enabled workflow orchestration and automation systems integrating AI models, CRMs, document systems, client portals, and internal tools; implement API/webhook integrations, vector retrieval, prompt orchestration, monitor reliability/performance, and ensure governance, compliance, and scalability.

Design, build, and maintain AI-enabled workflow orchestration and automation systems for legal service delivery. Implement integrations between AI platforms, CRMs, document systems, client portals, and payment systems. Develop event-driven pipelines, retrieval and prompt orchestration, agent workflows, and observability. Monitor reliability, troubleshoot integrations, support compliance and governance, and document architectures and operational standards.

Design and implement AI-native workflow orchestration and automation systems for legal services. Build integrations between AI models, CRMs, document systems, client portals, and operational tools; develop event-driven pipelines, retrieval and prompt orchestration, monitoring, and compliance controls. Collaborate with legal, product, and engineering teams to translate legal workflows into scalable, secure architectures and troubleshoot production issues.

Design and implement AI-native workflow orchestration and automation systems for legal services. Build integrations between AI models, CRMs, document systems, client portals, and internal tools. Develop agent workflows, vector retrieval and observability pipelines, monitor reliability and performance, troubleshoot integrations, and support governance, compliance, and scalable client experiences.

Design, build, and operate production agentic AI systems on AWS Bedrock AgentCore using Strands/LangGraph. Implement tool integrations (MCP/Gateway), evaluation pipelines and LLM-as-judge CI gates, observability, cost/latency controls, and guardrails for agents operating on live dealer data.

Build and scale AI-powered marketing skills, workflows and automations. Prototype and evaluate LLM tools, author and refine prompts, embed AI across campaigns, train teams, measure impact, maintain documentation, and establish governance and quality standards to ensure secure, compliant, and repeatable AI-driven marketing operations.

As a Staff AI Software Engineer at PromptQL, you'll lead the development of AI systems, design architecture, and optimize performance while shaping the direction of AI technology in enterprises.

The AI Special Projects Engineer will work cross-functionally to build features, automate workflows, and create demos for Lightning Labs, focusing on AI-driven solutions.

Design, build, and maintain AI-enabled applications and intelligent agents using Python and Java. Integrate LLMs, conversational AI, and ML models into enterprise systems, create APIs and microservices, ensure scalability and security, and collaborate with cross-functional teams to improve end-user journeys.

Architect and build AI-native production systems across a multi-language stack, design offline and online evaluation frameworks for LLMs, monitor live model behavior and drift, lead architecture reviews, mentor senior engineers, and prototype and ship AI capabilities while ensuring reliability and correctness in a regulated domain.

As a Senior Software Engineer at Vanta, you will design and build internal tools for go-to-market teams, focusing on applications that enhance sales and customer engagement, employing modern tech and AI workflows.

Lead technical adoption of AgentControl by building integrations, demos, and content; advise customers and partners; collect product feedback; develop Solutions Engineering playbooks; collaborate with product, engineering, and AI SME teams; evangelize at conferences; and measure activation, usage, and impact to drive product-market fit and revenue.

Lead and sustain large-scale HPC systems supporting NOAA/NWS forecasting. Manage scheduler/software stack (PBS Pro/Slurm), optimize performance and throughput, troubleshoot multi-node Linux clusters, develop scripts, and support 24/7 operations with occasional travel and on-call duties.

Serve as a technical advisor to research labs to accelerate adoption of NVIDIA AI and computing platforms. Map research ecosystems, track emerging scientific AI trends, collaborate cross-functionally, enable researchers through demos, workshops, and technical content, and represent researcher needs to inform product, education, and platform roadmaps. Attend conferences and foster long-term academic and national-lab partnerships.

Design and implement AI agent architectures and integrations for enterprise customers. Lead technical discovery, map systems and workflows, configure agent behavior, run QA/testing, and partner with Product/Engineering to optimize deployments and advocate product improvements.

Design, implement, and own a reusable on-device ML inference platform for resource-constrained devices. Integrate inference into RTOS firmware, develop drivers and DMA paths, debug on real hardware, train and optimize models for microcontroller-class hardware, and ship features to production while raising team expertise and using AI-assisted tooling.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Lead product development by identifying user pain points and building AI-powered solutions, while collaborating with teams to drive impact and iterate based on feedback.

Partner with customers to design and deliver production-ready AI/ML solutions, drive POC-to-production success, troubleshoot technical issues, inform product roadmap with customer feedback, and communicate outcomes to stakeholders.