Top AI Engineer Jobs

Design, build, and deploy production-grade generative AI features (RAG, embeddings, vector search, agents) for healthcare applications. Implement backend APIs, integrate AI into front-end interfaces, ensure HIPAA-compliant data handling, and establish evaluation, monitoring, and guardrails for safe, reliable AI in clinical and member-facing systems.

Design and implement AI-powered automation systems, build scalable backend services, make architectural decisions, and collaborate with product and data teams.

The AI-Native Data Platform Engineer will design data foundations for AI systems in wealth management, architecting data pipelines, models, and frameworks to enable autonomous financial agents.

Drive the architecture, design, implementation, and evaluation of AI systems and data platforms while mentoring teams and contributing to technical strategies.

As a Senior Software Engineer for AI Applications, you'll develop AI-native features, own backend systems, and ensure performance and safety in AI workflows.

Design and operate multi-petabyte, high-performance storage for large-scale AI/HPC clusters. Architect parallel filesystems and object stores, build Kubernetes-native storage operators, optimize RDMA/InfiniBand and NVMe-based data paths for 10–50 GB/s per node, implement multi-tier caching and prefetching, ensure observability and 99.9%+ uptime, and collaborate with ML/SRE teams while driving cost and performance improvements.

The Senior Data Engineer will design and maintain data architectures, work with operations teams, solve complex data challenges, and document decisions for stakeholders.

Develop and scale AI-powered features for Vendelux's platform, focusing on data-driven solutions and enhancing user experience in event marketing.

As a Senior Product Engineer, you will develop web applications, APIs, and AI workflows, collaborating from conception to delivery and owning the entire process.

The role involves delivering solutions to technical problems, optimizing APIs, transforming requirements into tasks, mentoring, and participating in hiring.

The Software Engineer will build AI-powered chatbot workflows, own features end-to-end, and collaborate in a fast-paced environment. Ideal candidates have a strong engineering foundation and experience with AI development tools, focusing on enhancing software processes.

Build AI-powered platforms and tools, focusing on backend services in Python, integrating LLM capabilities, and ensuring performance and reliability.

The AI ML Operations Engineer will design and manage machine learning systems from data collection to deployment, ensuring system reliability and optimizing workflows.

Design and maintain backend services, develop microservices, implement asynchronous processing, and collaborate on system scalability for AI-assisted applications.

The Senior Full Stack Engineer is responsible for developing backend services with Node.js and mobile applications using React and Capacitor, emphasizing code quality and architectural principles in a collaborative environment.

As a Staff AI Software Engineer, you'll design and build AI-native systems, lead model strategy decisions, and partner with product and engineering teams to deliver innovative AI solutions.

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.

As a Sr. AI Engineer, you will design and ship applied AI systems, make technical decisions, evaluate model behavior, and ensure MLOps ownership while contributing across the full stack and partnering with product teams.

As an AI Support Engineer, you'll handle customer issues, escalate unresolved problems, document failure modalities, and provide product testing feedback.

Embed with product/tech cohorts to build plugins, skills, hooks, and connectors; integrate tools via MCP Gateway and AWS; productize reusable patterns to the plugin marketplace; mentor engineers, measure adoption, and support on-call for published artifacts.

Design, build, and maintain scalable, secure AI core platform and web/data pipelines. Drive observability, auth/network integrations, runtime scalability, AI/ML infra for LLMs, mentor engineers, partner across teams, and ensure PHI security and compliance.

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.

Embed with product/tech cohorts to build and ship Claude Code plugins, skills, hooks, and MCP integrations; generalize work into reusable platform artifacts; integrate services via the MCP Gateway and AWS; support adoption, documentation, and on-call for marketplace artifacts while partnering on security, auth, and observability.

Lead the optimization and performance analysis of distributed training and inference workloads on NVIDIA GPU platforms, with responsibilities including debugging, benchmarking, and ensuring reliability of large-scale AI systems.

Drive benchmark results for GenAI inference, optimize performance across multiple models, and establish methodologies while leading technical initiatives in GPU performance engineering.