Top Remote AI Engineer Jobs

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.

Design and implement full-stack applications and AI agents for the GenAI platform, ensuring rapid development and deployment across critical industries. Collaborate with teams to deliver secure and reliable cloud-native systems.

The Lead Product Software Engineer will develop AI solutions, collaborate with teams, and lead projects focused on customer-centric product development using Agile methodologies.

Senior technical leader who architects, builds, and deploys Generative and Agentic AI solutions for enterprise clients. Leads client engagements, mentors technical teams, designs scalable ML/LLM pipelines and MLOps, facilitates workshops, and ensures best practices and responsible AI across projects.

Build and operate an on-prem AI platform (Model-as-a-Service) including RAG pipelines, vector DBs, MCP tooling, agent repositories, CI/CD integration, and guardrails within MRM. Optimize large on-prem GPU infrastructure and translate business use cases into scalable platform services.

Design, test, and document prompts and prompt libraries to optimize AI language model outputs. Collaborate with product, data, and ML engineers to integrate prompt solutions, run A/B experiments, measure performance, and maintain versioned documentation. Support TIBCO-specific implementation and stay current on AI/NLP techniques.

Design, develop, and deploy machine learning and deep learning models; build end-to-end ML pipelines including preprocessing, training, evaluation, and deployment; perform feature engineering on large datasets; deploy and monitor models on cloud platforms; collaborate with cross-functional teams to integrate AI solutions and retrain models as needed.

Operate and monitor ML/AI models and agentic systems in production. Build AI observability, logging, tracing, and evaluation pipelines. Monitor LLM outputs, detect drift and model degradation, and maintain data/feature pipelines. Develop CI/CD, model versioning, experiment tracking, and automate alerts and incident remediation while collaborating with data scientists and platform teams.

Design, develop, fine-tune, and deploy generative AI models using deep learning and transformer architectures. Collaborate cross-functionally, troubleshoot model issues, optimize performance, document work, and communicate technical concepts to non-technical stakeholders.

Design, build, and deploy production-grade ML and AI systems end-to-end, combining classical ML, deep learning, and LLM/agentic integrations. Implement MLOps, monitoring, CI/CD, model serving, vector search/RAG pipelines, and scalable APIs; mentor engineers and drive engineering best practices.

Entry-level developer working with Python or JavaScript to design, build, test, and maintain software. Collaborate with senior developers, participate in code reviews, debug, and learn new technologies while contributing to the full software development lifecycle.

Design, develop, fine-tune, and deploy generative AI models (GANs, VAEs, transformers). Collaborate with cross-functional teams, troubleshoot model issues, document work, and communicate technical concepts to non-technical stakeholders while staying current on research.

Design, deploy, and optimize cloud-native ML systems on AWS, integrate foundation models (Bedrock/Anthropic), build and monitor SageMaker pipelines and data pipelines, detect drift, extend ML infra and libraries, and collaborate cross-functionally to deliver secure, cost-efficient production ML services.

The AI Product Engineer will design, build, and ship AI features for clean energy finance while collaborating with various stakeholders to improve transaction processes.

Design, build, and operate scalable integrations and AI agents using Celigo integrator.io, LangChain/LangGraph and modern cloud data pipelines. Collaborate with business stakeholders to automate processes, ensure data quality and security, own integrations end-to-end, produce technical documentation, and support operational hand-offs.

Design, build, and ship LLM-powered features end-to-end for an EHR platform. Build evaluation, observability, and reliability for AI workflows, handle PHI safely, enable other product teams via tooling and patterns, and pair on implementation from prototype to production while enforcing responsible AI practices.

Design, build, deploy, and operate production-grade AI/ML and LLM systems (including RAG and agentic pipelines). Integrate AI capabilities with product workflows, run evaluation and monitoring, optimize model and system performance, and apply strong engineering practices (testing, CI/CD, versioning).

As a Staff Data Engineer, you'll architect and build data pipelines, champion small data strategies, mentor teams, and ensure operational excellence in data workflows.

Design and implement a virtual access layer to enable remote use of a physical AI lab, building scalable, secure infrastructure to process 100,000+ documents/day with LLMs, optimize GPU/LLM throughput, provide customizable interfaces, implement authentication/access controls, and lead projects from design to production.

Design and develop a C++-based system for simplifying and accelerating computing in DL and HPC, alongside evaluating performance and improving library quality.

Customer-facing technical role supporting AI/ML initiatives across US Major Accounts. Architect and prototype AI/ML solutions, build MVPs and PoCs, support regional SE teams, deliver technical presentations and workshops, and upskill teams. Travel ~30-40% to support customer engagements.

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.