Top AI Engineer Jobs

As an Applied Gen AI Engineer, you'll design and deploy generative AI systems for code review, collaborating to enhance developer productivity through advanced workflows and models.

As an Applied AI Engineer, you will develop advanced multimodal AI systems focused on voice interactions, ensuring compliance with financial regulations and implementing safety frameworks.

Design and deploy end-to-end AI workflows to automate sales, marketing, and e-commerce. Build full-stack applications and APIs (ReactJS, Go/Rust, Python), integrate Salesforce/Marketo and data warehouses (Azure, Oracle Exadata), implement LLM orchestration and prompt engineering, and construct scalable data pipelines for real-time AI-driven insights.

The Lead Full Stack and AI Developer will design and implement AI/ML solutions and cloud-native applications on Azure and ensure secure coding practices. Responsibilities include mentoring teams and collaborating on technical concepts for customer-driven projects.

The Agentic AI Software Engineer develops and maintains software for Agentic AI platforms, implements integrations, collaborates with architects and customers, and manages deployments in a fast-paced environment.

Lead the design and architecture of AI agent systems for monetization, develop machine learning models, and mentor junior engineers.

The Founding AI Engineer will develop cloud native services, manage deployments on Kubernetes, and write production-ready agents, requiring strong skills in Python and TypeScript.

Hands-on technical leader who architects and builds production AI systems (LLM orchestration, retrieval, agentic workflows, structured reasoning). Drives architecture, monitoring, evaluation, and governance; mentors senior engineers and ships large-scale, reliable AI services.

Build and maintain AI tools for internally at Automattic, focusing on enhancing productivity through LibreChat while collaborating with the team.

The Applied AI Engineer will develop and ship AI features across Automattic's products, collaborating with teams and scaling innovations that impact millions of users.

The Senior AI Engineer will lead AI initiatives, design advanced AI systems, mentor engineers, and develop end-to-end AI solutions using various technologies and tools.

Translate multi-modal AI research into 0-1 products: design and run ML experiments, build scalable training and evaluation infrastructure, implement MLOps and data pipelines, deploy models, and use AI code tooling to move experiments to production MVPs.

The Senior Machine Learning Engineer will develop and maintain algorithms/services for multi-agent AI, deliver cloud-native architecture, and optimize ML models for performance.

The AI Engineer will develop and deploy large language models, build infrastructure for high-throughput AI systems, and collaborate with product teams to integrate AI capabilities.

Design and build a unified evaluation platform and automated pipelines to evaluate LLM-based agents at enterprise scale. Implement observability, tracing, feedback loops, and guardrails; integrate LLMs, retrieval, embeddings, and orchestration; partner with product and ML teams to turn production failures into evaluation cases.

Lead the development of AI/ML systems for document processing, mentor engineering teams, and implement advanced machine learning solutions focused on language models and data extraction.

Design and build autonomous, enterprise-grounded AI agents and workflows using the Elastic Stack, RAG, and LLMs. Integrate models with internal APIs and SaaS, manage deployment and scaling on cloud/Kubernetes, ensure security/compliance, document systems, and provide technical leadership for agent lifecycle and performance optimization.

The Senior AI Engineer will develop AI solutions for incident management, collaborate cross-functionally, and enhance observability tools through iteration and ownership.

Lead the development of AI for a multiplayer RPG, overseeing architecture, mentoring engineers, and aligning AI with creative visions. Drive innovation and ensure high-quality game experiences.

Drive the design and integration of Generative AI solutions, collaborating with teams to optimize AI models and support production environments.

Lead the development of AI/ML solutions for government missions, providing technical direction, evaluating emerging technologies, and overseeing implementation while ensuring compliance with DoD standards.

Participate in a work-integrated program combining structured learning with real work in software engineering and data science. Complete boot camps while contributing to actual projects and receiving mentorship.

Apprentices will complete a bootcamp in Data Science & AI while working on software projects, writing code, and collaborating with experienced developers.

As a Full-Stack AI Engineer, you will design and develop AI-driven applications, manage backend services, optimize data management, and ensure engineering excellence in an Agile environment.

The AI Engineer designs, develops, and deploys AI applications to enhance healthcare workflows, automate processes, and support data-driven decisions, collaborating in a team to create scalable cloud-based systems.