Top Remote AI Engineer Jobs

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.

This role involves designing, developing, and maintaining AI/ML products, collaborating with stakeholders, and ensuring model deployment on AWS. Responsibilities include creating APIs, establishing MLOps practices, and driving AI strategy for operational improvements.

Develop and productionize AI/ML systems across the full lifecycle: design agentic workflows, integrate models into applications, implement multi-agent orchestration, build data pipelines, write scalable code, monitor and optimize production AI, and collaborate with cross-functional teams.

Early-career full stack internship developing frontend and backend features under senior guidance. Integrate AI coding tools into workflows, translate product requirements to implementations, contribute across the product lifecycle, and suggest cross-team process improvements while learning full-stack practices.

Early-career full stack engineer role to build end-to-end product features, integrate AI coding tools into the workflow, mentor peers, improve cross-team efficiency, and contribute across the product lifecycle from design through deployment.

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.

The role involves optimizing analog-aware software for neural networks, designing algorithms, improving software quality, and collaborating on hardware validation. Requires experience with complex algorithms and communication skills.

Build end-to-end AI integrations in a cybersecurity platform: gather contextual security data, call and optimize AI services, map responses to actionable UI (React), implement error/fallback handling, monitoring, caching, and user feedback loops while working directly with customers.

Build, deploy, and optimize production AI/ML and LLM-driven decisioning systems for claim offer generation and negotiation. Own end-to-end model development, evaluation, experimentation, and operational reliability while balancing fairness, business objectives, and product requirements.

Owner of the marketing intelligence stack: build warehouse-backed data models, integrate intelligence and CRM tooling, ship CEO-facing GTM dashboards, and design agentic LLM workflows (on Claude) for briefs, content, and account monitoring while ensuring compliance and observability.

Lead design, development, and deployment of AI-enabled full-stack web applications on AWS. Own frontend (React), backend (Java/Python), APIs, workflow orchestration, RDBMS, CI/CD, DevSecOps, accessibility, and data visualization. Implement AI features (search, chatbots, document processing), mentor engineers, conduct code reviews, and work within SAFe to deliver secure, scalable mission solutions.

Design, build, and deploy production-ready agentic AI and multi-agent systems to automate enterprise workflows. Integrate agents with enterprise platforms (APIs, OAuth2, webhooks), prototype solutions, implement guardrails and observability, and deliver scalable automation primarily for marketing operations. Collaborate with clients and cross-functional teams, provide technical leadership, and produce reusable integration and orchestration patterns.

Design, build, deploy, and operate production-grade AI/ML solutions and LLM-powered, agentic applications across Azure, AWS, and hybrid environments. Implement end-to-end pipelines (ingestion, prompt engineering, deployment, monitoring), integrate with enterprise data platforms, ensure security/privacy compliance, and collaborate with engineering and business teams to support lifecycle management and production support.

Build and ship backend product features powering AI-driven user experiences: design APIs and services, implement agent-driven logic (context retrieval, action execution, conversation management), ensure reliability and observability, collaborate with AI engineers and product teams, diagnose performance bottlenecks, and contribute to architecture and rollout decisions.

Design, build, and maintain AI platform infrastructure and services. Implement scalable backend systems, REST APIs, CI/CD, observability, automated testing, and cloud-native streaming. Collaborate across teams, apply TDD, and use generative AI tools to accelerate development.

Design and build core backend systems for an agent platform: orchestration, durable execution, memory, tool integration, observability, and evaluation. Create scalable services/APIs, develop retrieval and long-term memory solutions, monitor and improve agent behavior, and help drive technical direction and team growth for AI-driven collaboration features.

Lead architecture and delivery of an internal AI/agent platform used across product teams. Design agent runtimes and SDKs, define release gates (evals, safety, telemetry, AuthX), set standards for prompt management and model selection, partner with product teams to integrate reusable platform capabilities, write and ship production code, and mentor engineers to raise company-wide production quality for agentic systems.

The role involves researching and developing GPU-accelerated AI workloads, optimizing algorithms, and collaborating with technical experts to improve hardware performance.

The Senior Full Stack Engineer will design and operate identity systems, implement AI-driven efficiencies, mentor engineers, and ensure high-quality code in an AI-first environment.

Embed with enterprise clients to discover user needs and build AI-powered full-stack features (React/Next.js frontend, Python/Node backend). Rapidly prototype, integrate LLM APIs, harden for production, iterate with users, and contribute to internal libraries and standards.

Sola seeks a Software Engineer for Desktop Automation to own and enhance their execution platform, focusing on reliability and integrating with AI pipelines.

As a Senior Software Engineer, you'll collaborate to build and maintain automation capabilities, contribute to AI solutions, and ensure scalability, improving the user experience with software solutions.

Post-sales, customer-facing role that drives developer adoption of AI tooling by designing and running hackathons, Customer Developer Days, and repeatable facilitation infrastructure. Partner with deployment and success teams to diagnose adoption stalls, run high-touch interventions, capture outcomes, and evangelize results. Must be technically credible with developers and able to troubleshoot and demonstrate AI coding tools in real time.

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.