Top Remote AI Engineer Jobs

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.

Design, implement, and scale web and data pipeline solutions focused on generative AI and LLMs. Improve AI/ML infrastructure for model development, training, deployment, and prompt engineering. Partner with product and stakeholders to prioritize applied AI use cases, ensure PHI security and regulatory compliance, mentor junior engineers, and contribute APIs and integrations to embed generative AI into healthcare applications.

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.

Build LLM-powered full-stack features: vector-backed expert and solicitation indexes, search (OpenSearch/PGVector), APIs and UI. Ship production-quality Python/Go and React code, using AI tools daily, ensure security, reliability, and scalability while iterating rapidly on an AI-first platform.

The AI Software Developer will design, craft, and optimize AI prompts, moving prototypes to operational systems, and architect scalable infrastructures for agentic AI systems.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

As a System Engineer, you'll design, deploy, and maintain cloud systems for AI workloads, troubleshoot complex issues, and collaborate with teams to optimize performance.

Design, build, and operate production AI platform capabilities and agentic workflows. Collaborate on architecture, write production-quality backend code, mentor developers, troubleshoot production issues, and drive adoption of reusable AI frameworks, MLOps practices, and cloud-native intelligent services across a multi-tenant SaaS dental platform.

Design, build, test, deploy, and maintain production AI capabilities (agents, workflows, models, MCP servers, APIs) across a SaaS dental platform. Train and operate ML models, implement RAG and vector DB solutions, use AI-assisted tools, collaborate in design and code reviews, and support production reliability and monitoring.

The role involves synthesizing, placing, and routing high-speed designs, collaborating with RTL teams, and optimizing designs for power/performance area.

Primary point-of-contact for a customer, providing on-site and remote HPC, Ethernet, and AI infrastructure support. Troubleshoot Linux systems, networking protocols, and interoperability; reproduce and resolve complex issues; collaborate with engineering, marketing, and support; document support methodologies and improve processes.

The AI Go-to-Market Engineer will deploy, train, and optimize AI systems across Flosum's revenue operations to enhance productivity, automate processes, and drive efficiency while working directly with the CEO.

Design, build, and operate an enterprise AI platform: automate provisioning with IaC, deploy zero-downtime cloud services, enforce security and observability, review code, mentor engineers, and participate in 24/7 on-call rotation.

Lead design, build, and deploy scalable Generative AI and ML systems into production. Implement LLM integration, prompt engineering, RAG, conversational interfaces, model monitoring, evaluation frameworks, APIs, inference optimization, and collaborate to productionize forecasting and ML models.

The role involves building and maintaining AI data capabilities, implementing data pipelines, and ensuring operational excellence in data management within a healthcare context.

Own end-to-end AI-powered product improvements: design and build cross-cutting AI services (retrieval, evaluation, guardrails), define success metrics, prototype to production, create shared AI tooling and abstractions, shape data and system architecture for safe longitudinal signals, mentor engineers, and ship reliable, secure production systems that improve educator and family outcomes.

Lead technical design and delivery of scalable, cloud-native SaaS solutions. Drive architecture and implementation across frontend and backend stacks, mentor engineers, apply AI/agent workflows and NLP, ensure high availability, and collaborate with product and cross-functional teams to ship reliable, production-grade systems.

The Senior .Net Developer will enhance SDG's C#/.NET Core codebase, design high-load services, and optimize MS SQL queries, benefiting from a remote work environment and attractive benefits.

Architect, build, and operate Redpanda’s Agentic Data Plane and cloud services across AWS, GCP, and Azure. Lead large technical projects, define architecture, develop automated provisioning and self-healing systems, and ensure reliability, scalability, security, observability, and zero-downtime upgrades. Participate in on-call operations, mitigate technical risks, and collaborate across engineering, product, and customer-facing teams.

Build and operate AI-powered automations for HVAC businesses. Map undocumented workflows, design improved AI-enabled processes, create specifications, configure workflows, monitor production runs, troubleshoot failures, add error handling and fallbacks, and identify reusable patterns across customer accounts. Lead discovery and implementation discussions with business owners and office managers while feeding field insights into the product roadmap.

Build end-to-end software features across frontend, backend, and AI components. Responsibilities include developing interfaces, APIs, backend services, data pipelines, automation workflows, and LLM-powered applications such as RAG systems and AI agents. The role involves testing, documentation, debugging, cross-functional collaboration, product iteration, and using AI coding tools to improve development speed and quality.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

Technical lead for third‑party AI tool connectivity and custom MCP servers. Design secure AI integration architecture, build and operate connectors, lead incident response, automate lifecycle and monitoring, integrate with identity and security systems, mentor engineers, and drive cross‑functional onboarding and rollout of AI integration standards.

Build AI agent discovery across Azure, endpoints, and future AWS and Google Cloud environments. Assess agent configurations, access, and security risks, then integrate findings with Delinea’s identity and attribution platform for governance. Extend existing discovery services, collaborate with platform teams, and solve complex backend engineering problems using cloud APIs and modern backend languages.