Top Remote AI Engineer Jobs

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.

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.

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

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.

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.

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.

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.

Build and scale production enterprise AI applications using RAG, LLM integrations, agents, vector search, and prompt evaluation. Develop Python/FastAPI backends, React/Next.js frontends, real-time services, and database architectures. Deploy AI workloads with Docker, Kubernetes, CI/CD, cloud infrastructure, and Terraform. Implement monitoring, testing, security, observability, and cost optimization for reliable, scalable AI systems.

Work with a business domain to map workflows, design agent-driven workflows, build and integrate agent and automation pipelines, deploy and run agents in production, monitor KPIs and observability, and iterate with human-in-the-loop checkpoints to reliably improve business outcomes.

Designs, deploys, maintains, and tunes large-scale HPC and AI clusters. Responsibilities include workload scheduling, infrastructure automation, CI/CD pipelines, monitoring, logging, alerting, storage and networking deployment, bottom-up troubleshooting, methodology documentation, and R&D support. The engineer works across hardware, operating systems, GPU computing, virtualization, cloud platforms, and software stacks to deliver performant, reliable self-service infrastructure.

Design and scale Zip’s enterprise data and AI platform across batch, streaming, structured, and unstructured workloads. Build reliable pipelines, AI-ready data products, semantic models, vector and hybrid search, and RAG capabilities. Establish standards for modeling, testing, governance, security, observability, and automation. Partner with engineering, data science, product, and business teams while mentoring engineers and influencing platform architecture.

Lead technical design and hands-on execution for complex products and systems. Design scalable architectures, write and review code, solve production issues, make technical trade-offs, mentor engineers, improve engineering practices, and drive initiatives from problem definition through production. Collaborate with product, design, and AI teams while owning system reliability, security, testing, observability, and continuous improvement in a distributed global environment.

Lead technical design and execution for complex products and engineering initiatives. Build scalable systems across backend, frontend, APIs, databases, and infrastructure while remaining hands-on with coding, reviews, debugging, and production support. Set standards for architecture, reliability, security, testing, and observability; mentor engineers; identify technical risks; improve tooling and automation; and collaborate with product, design, and AI teams to ship high-quality products.

Lead technical design and execution for complex products and engineering initiatives. Build scalable systems, write and review code, make architecture decisions, debug production issues, improve reliability, mentor engineers, and collaborate with product, design, and AI teams. The role requires end-to-end ownership from ambiguous problem definition through production, with strong product judgment and hands-on technical leadership.

Develop backend systems for 3D AutoReview, including geometry parsing, model analysis, quality detection, rule systems, scalable APIs, and AI-assisted review workflows. Collaborate with backend, frontend, product, and machine learning teams to deliver production features. Build extensible systems for custom 3D rules and reference data while experimenting with CAD, machine learning, and large language model technologies.

The role involves developing scalable backend systems in Go and other languages, building high-volume analytics, and designing APIs for ML workflows.

As a Senior AI Product Engineer, you will build scalable services and front-end applications, design APIs, and enhance AI product offerings, focusing on improving user experience and collaboration with engineering teams.

Senior DevOps engineer building AI-powered agents, automation pipelines, and full‑stack business applications. Design and maintain integrations (SAP, Salesforce, Google Workspace, Slack, Jira), REST APIs, CI/CD, and containerized deployments. Lead AI standards, prompt engineering, agent frameworks, cross-functional discovery, documentation, and enablement while helping grow an AI Automation & Integrations practice.