Top Remote AI Engineer Jobs

Integrate LLMs, RAG, and agentic-AI into secure decision-support software. Design prompts and inference workflows, connect AI to backend services, evaluate outputs, build tests, document designs, and collaborate with engineering, security, and DevSecOps teams to deliver reliable mission-capable AI features.

The Staff ML/AI Platform Engineer will design, prototype and deploy AI/ML models, optimize pipelines, mentor junior engineers, and collaborate closely with other teams to develop machine learning solutions.

The Principal Software Engineer will lead the design and build-out of an AI Context Layer, ensuring high-quality data for AI systems, while managing access control and developer interfaces, and leading cross-team projects.

Design and build secure, cloud-native AI applications using LLMs, RAG, and Amazon Bedrock to provide AI-assisted search, summarization, and clinical question-answering; integrate with enterprise healthcare systems using FHIR/HL7, implement vector search and prompt orchestration, ensure Fed security/privacy compliance and CI/CD, and support testing, monitoring, and governance for production readiness.

Embed with strategic higher-education partners to design, build, and ship production AI and platform integrations (LLM/RAG, LTI) across Cengage products. Own end-to-end deployments, write production code, ensure compliance and accessibility, evaluate AI safety and outcomes, mentor FDEs, and translate field learnings into product roadmap contributions.

Lead technical discovery and solution design for enterprise MedTech customers, translate claims data into commercial insights, deliver data via secure sharing/APIs/warehouses, own RFPs and security reviews (SOC2/HIPAA/BAA), enable demo environments and AI narratives, and institutionalize best practices across Sales, Product, Data, and Engineering.

Lead technical architecture and delivery of end-to-end AI solutions across the Workday ecosystem. Design data flows, integrations, security and RAG/LLM patterns; advise executive stakeholders; lead technical workstreams; collaborate with Product and Engineering; ensure privacy, ethical AI, and scalable deployments for complex global customers.

Lead developer advocacy for AI and agentic security: advise security companies, accelerate NVIDIA stack adoption, guide partner integrations, map ecosystems, collaborate cross-functionally, run community events, and feed product teams with field insights.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

Design, build, and maintain scalable enterprise full-stack applications using Java, Spring Boot, microservices, and modern front-end frameworks. Implement cloud-based solutions on AWS, contribute to CI/CD and DevOps automation, optimize performance and security, and integrate AI-driven capabilities using Python and orchestration tools like LangChain and LangGraph.

Build and improve production AI systems that extract structured data from legal documents into a household knowledge graph. Own and design evaluation suites, improve agent orchestration and tooling, create human-review workflows, and ship dependable, scalable changes to production while collaborating with domain experts and product.

Lead design, deployment, and scaling of enterprise DLP across cloud, endpoint, SaaS, and network with a focus on AI-driven automation. Build automated classification, remediation, and workflows, integrate DLP with SIEM/SOAR/identity/cloud, develop policies for regulatory compliance, mentor engineers, and present program insights to leadership.

Lead design and rewrite of cloud-native core systems. Build scalable back-end services and front-end features, drive architecture and testing discussions, mentor engineers, and improve telemetry, performance, and reliability.

Build, operate, and scale cloud-native backend services and APIs for a high-volume vehicle marketplace. Embed AI-driven capabilities into features, use AI tools to accelerate development, participate in on-call rotations, improve reliability, and collaborate with Product, Data, Infrastructure, and SRE teams to deliver production-ready systems.

Lead enterprise strategy and engineering to defend against AI-powered threats. Design detection, prevention, and response architecture for adversarial AI, integrate controls into cyber tooling, build threat models, prototype defensive AI, and mentor teams while influencing leadership and vendor selection.

Design, build, and operate secure cloud CI/CD pipelines and automation (Ansible, Terraform, Packer). Lead identity governance for AI/non-human identities in SailPoint, automate access reviews/certifications, collaborate with InfoSec and platform teams to enforce controls, troubleshoot production issues, and drive centralized agent identity governance across cloud environments.

Designs and implements secure, fully automated CI/CD pipelines and identity controls for cloud deployments. Builds infrastructure-as-code (Ansible, Terraform, Packer), integrates identity and auth (AWS IAM, Azure/Entra ID, SailPoint, OAuth/OIDC/SAML/SCIM), and automates guardrails for non-human identities and agent workloads. Partners with architecture, InfoSec, and engineering to ensure compliance, observability, and scalable, secure deployments.

Design, build, and operate secure cloud CI/CD pipelines and automation (infrastructure as code) to support cloud deployments. Partner with InfoSec, architecture, and engineering to enforce identity and non-human identity governance, implement IAM integrations, secrets management, and automated guardrails. Troubleshoot production pipeline issues, develop tools to reduce errors, and research technologies to improve DevSecOps effectiveness.

Lead design and implementation of scalable SaaS applications with advanced AI features (semantic search, vector DBs, RAG, LLM orchestration). Translate business needs into technical designs, mentor engineers, enforce code quality and CI/CD, champion AI-assisted tooling, and drive architectural integrity and developer experience across the organization.

Own full sales and partnership cycle to bring voice AI to mobile service robots: engage senior robotics decision-makers, qualify and prioritize opportunities, close deals, and shape the commercial playbook while operating autonomously within a small technical team.

Lead and operate enterprise Azure and Microsoft 365 platforms, manage hybrid identity (Entra ID/AD), deliver and govern AI solutions (Azure OpenAI, Azure ML, Copilot), provide L2/3 support, secure and govern cloud resources, manage on‑prem infrastructure, and drive vendor, project, and stakeholder engagement to scale AI initiatives.

Build and maintain cloud infrastructure and observability for scalable systems. Monitor, troubleshoot, patch, and automate operations using IaC, CI/CD, Kubernetes, and AI-driven automation. Manage backups, disaster recovery, log pipelines, databases, and message streaming. Collaborate with engineering, security, and business teams to improve reliability, incident response, and infrastructure lifecycle (including Terraform state cleanup and decommissioning).

Designs, builds, and operates GenAI cloud platforms across Azure, AWS, and Google. Develops self-service tools, CI/CD pipelines, and Terraform IaC. Troubleshoots performance and availability, automates deployments, supports developer adoption of LLMs and AI services, and leads postmortems and scalability planning.

Drive enterprise adoption of Generative AI and LLMs by discovering and prioritizing use cases, enabling teams via training and coaching, configuring and supporting AI workflows and agents, collaborating with technical and compliance teams, and establishing governance and success metrics.

Design and build data infrastructure and AI/ML systems—extracting, cleaning, moving, and storing data; develop, deploy, and monitor ML and LLM-based products; build APIs; collaborate with stakeholders and manage projects to meet business needs.