Top Remote AI Engineer Jobs

Lead architecture and evolution of Juniper Square’s distributed services, cloud infrastructure, and developer platform. Design scalable, multi-tenant, event-driven systems; build paved-road developer tooling, CI/CD, and observability. Hands-on coding, prototyping, and performance troubleshooting. Enable production AI/LLM workloads, ensure security/compliance, support enterprise upmarket needs, and mentor engineering teams to raise operational excellence and reliability.

Design and implement AI-driven applications using Verint technology, working with cross-functional teams to enhance customer experience and operational efficiency.

As a Principal Software Engineer, you will architect AI-enabled systems, mentor teams, and guide technical decisions for scalable products.

The Gen AI Data Engineer will design and build distributed data systems, develop data pipelines, manage data infrastructure, and integrate technologies for real-time and batch processing, contributing to scalable analytics solutions.

Design, build, test, deploy, and maintain cloud-based applications, microservices, and infrastructure. Ensure application performance and quality, fix bugs, write automated tests, and collaborate on new features. Use AI-assisted development tools daily and implement IaC and modern architecture patterns to deliver secure, maintainable code.

Design, build, and operate secure enterprise AI platform capabilities connecting models, agents, and internal systems. Own major infrastructure workstreams (MCP gateway, enterprise context), build backend services and APIs, enable identity-aware governance (access, permissions, auditing), design agentic workflows, and take operational ownership while partnering with stakeholders to scale dependable AI tooling across Spotify.

Work with customers to discover high-value AI use cases, design and prototype LLM- and agent-based solutions, build demos and pilots, and support transition to production. Provide technical architecture, documentation, training, governance guidance, and hands-on implementation support across integrations, automation, and evaluation to enable secure, explainable, and measurable AI adoption.

Six-month early-career internship building LLM-powered agent workflows and production AI components. You'll design prompts, retrieval and tool-use logic, run benchmarks, improve quality/latency/reliability/safety, contribute to backend services/APIs, and ship working prototypes alongside full-time engineers.

The Applied AI Software Engineer will evaluate LLM-based agents, manage benchmarking, and ensure performance, safety, and reliability in healthcare settings. Responsibilities include designing evaluation plans, running experiments, collaborating with teams, and developing internal tooling for AI features.

Design, develop, and evaluate AI safety assessment systems focused on LLMs and NLP. Investigate incident reports, conduct literature reviews, create and run NLP/LLM assessments, code or train text analytics, document methods, publish research, and collaborate with engineering teams to scale assessment tools.

Build, productionize, and operate AI-driven features and integrations across frontend, backend, and model layers. Prototype and deliver agent-driven experiences (conversational interfaces, RAG, tool-calling), integrate LLMs and external data sources, and collaborate with product and design. Participate in on-call/standby duties.

Design, build, and operate scalable backend services and internal APIs for an AI platform. Integrate LLMs and AI tools into production workflows, ensure platform reliability via observability and incident response, optimize AI runtime performance and cost, and contribute to shared infra like CI/CD and deployments.

The Principal AI/ML Engineer will lead the development of AI/ML platforms, drive technology architecture, ensure quality and integration, and provide strategic leadership while managing a team of engineers.

Lead execution of Product Engineering AI and automation initiatives across photonics products. Build and deploy reusable AI/automation tools, transform engineering data into AI-ready systems, and drive cross-functional adoption to improve development, qualification, manufacturing, and reliability processes.

Support development of internal LLM-based tools (coding assistants, RAG pipelines, prompt optimization), improve engineering efficiency, test and document AI tools, and research emerging AI technologies.

Early-career role building AI-powered developer tools and internal LLM applications. Tasks include coding assistants, lightweight RAG pipelines, prompt optimization, testing, documentation, and researching emerging AI technologies to improve engineering productivity.

Lead online brand reputation by owning page-one search results, producing SEO-optimized content, building PR relationships, launching customer advocacy, and executing rapid-response campaigns during reputation attacks.

As an AI Native Forward Deployed Engineer, you'll bridge customer operations and product development, implementing technical solutions and enhancing the platform based on field insights.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

The role involves leading the design and delivery of multi-agent systems for underwriting and claims automation, ensuring production readiness and business alignment.

The Senior Back End Software Developer will design and develop cloud notebook applications, focusing on back-end systems while collaborating on features and implementing secure interfaces and services.

The Senior Front End Software Developer will create secure, performant, cross-platform applications, collaborate on feature implementations, and ensure code usability and testing, with a focus on design and structure.

The AI Automation Engineer will automate internal processes, mentor non-technical staff on building tools, and ensure solutions deliver measurable business impact using AI technologies.

As a Full Stack Engineer III at Calendly, you'll develop features, scale the platform, and mentor team members while using various technologies.