Top Remote AI Engineer Jobs

Design and build internal platforms, tooling, and AI-powered workflows to reduce developer friction, improve velocity, quality, and reliability. Partner with product, infra, and security to create reusable paved paths, measure impact with engineering metrics, and help define the Developer Experience practice.

Design, build, and deploy Tier Zero self-service solutions (virtual agents, chatbots, automated troubleshooting), intelligent routing, and predictive maintenance. Integrate automation with ITSM platforms, use low-code/pro-code tools (e.g., Power Automate), track deflection and satisfaction metrics, ensure accessibility compliance, document architectures and runbooks, and coordinate with service desk and cloud teams to drive continuous improvement.

Embed with a business domain to map workflows, design agent-enabled future-state processes, build and connect production automation (LLMs, agents, RAG), run and monitor agents with observability and evals, and partner with domain leaders to deliver measurable KPI improvements.

Design, build, and deploy reliable, outcome-driven AI systems and agentic workflows that plan, reason, and act across enterprise systems. Integrate LLMs into production, work with structured and unstructured data to ground models in business context, and partner with product to ship end-to-end capabilities.

Design, build, and operate AWS-native AI/ML systems: RAG pipelines, fine-tuned LLMs, and microservices. Implement IaC (Terraform), CI/CD, policy guardrails, and production deployments integrating Bedrock/SageMaker, LangChain, and telemetry for secure, scalable enterprise use.

The AI Engineer will develop scalable AI systems, optimize LLMs, maintain data workflows, and ensure system resilience while collaborating on innovative solutions.

The AI Engineer will build AI-powered applications, prototype solutions, implement workflows using LLMs, and manage sub-projects while improving internal tools.

Design, build, and operate customer-facing AI systems through discovery, prototyping, deployment, monitoring, and scaling. Translate ambiguous problems into technical specs and prototypes, own system architecture and tradeoffs, collaborate with product teams, and improve tooling using frontier models and cloud platforms.

The Applied AI Engineer will develop AI-powered systems to streamline internal processes, collaborating with various departments to enhance efficiency and automation. This role involves problem ownership, system design, and deploying solutions that leverage AI technology while ensuring user adoption and long-term value.

As a Senior AI Engineer at BioRender, you'll develop AI-driven features, collaborate with cross-functional teams, and prototype innovative solutions to enhance scientific communication.

Build and own end-to-end AI features across the stack: prompt engineering, evals, vector search, backend/data models, and frontend interactions. Ensure accuracy, safety, speed, and on-brand AI outputs. Collaborate with Product and Design to iterate on generative AI features used daily (coaching, candidate summaries, natural-language assistant).

Design and implement AI-driven tools to improve workflows across teams. Collaborate to identify internal problems AI can solve, and prototype solutions quickly.

Build and deploy AI-powered tools and workflows across performance marketing, creative production, CRM, landing pages, growth operations, and product. Develop LLM integrations, personalization systems, automation pipelines, dashboards, Slack bots, and internal tools using marketing platforms and data infrastructure. Partner with Growth, Product, and Engineering teams, evaluate AI tooling, mentor nontechnical users, and translate technical solutions into measurable business impact.

Own the design and front-end implementation of Chess.com’s internal growth, AI knowledge, agent, and admin platforms. Create polished UI/UX, translate designs into production-ready interfaces, improve interaction and motion quality, and evolve the design system. Prototype rapidly with Cursor and Claude, design AI-native workflows, collaborate across a distributed team, review code, and ship end-to-end frontend experiences.

Own strategic enterprise deployments of production agentic AI systems, including multi-turn voice and digital agents, retrieval pipelines, integrations, guardrails, monitoring, evaluation, and ROI measurement. Support pre-sales demonstrations and proof-of-concept builds while translating customer feedback into product and engineering roadmap improvements. The role requires hands-on production coding, customer-facing technical leadership, and comfort operating in an emerging forward-deployed engineering function.

Build and scale an AI-powered audit workbench that transforms raw evidence into reviewable workpapers. Responsibilities include designing ingestion and extraction pipelines, deterministic recomputation and exception detection, workpaper generation, evaluation infrastructure, and frontend review tools. The role emphasizes production LLM reliability, golden-dataset evaluations, schema design, traceability, deterministic regulatory logic, structured human review, and end-to-end system ownership in a regulated domain.

Lead AI initiatives, establish strategy, and develop generative AI applications. Collaborate with teams to build and optimize financial products.

Lead design and implementation of high-performance agent runtimes, backend services, and self-hosted model/agent infrastructure. Build low-latency execution systems, real-time data pipelines, telemetry loops, CI/CD for zero-downtime deployments, and ensure fleet reliability on AWS/EKS.

As a Junior Backend Developer, you'll translate UI/UX designs into code, integrate with APIs, and utilize AI tools for efficiency.

Design and implement AI-driven solutions, collaborate with stakeholders, and scale AI knowledge across the organization. Foster AI adoption and develop scalable frameworks.

As an AI Product Engineer, you will develop and deploy AI-driven software solutions, collaborate with customers, and optimize applications for real-world impacts.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

Design, build and ship native Android features using Kotlin and Jetpack Compose. Integrate REST APIs, improve performance and reliability, debug production issues, and create AI-assisted on-device experiences (TensorFlow Lite). Collaborate with product and design to simplify complex financial user journeys.

Design, build and ship native Android features for an AI-enabled neobank using Kotlin. Improve UX, performance, reliability and integrate backend APIs. Collaborate with product and design to simplify user journeys and use analytics and production data to iterate on mobile experiences.

Lead architecture and build scalable, secure production services while championing AI-native development. Mentor engineers, influence technical direction, review PRs, and help evolve a legacy monolith to a modern stack in partnership with product and exec leadership.