Top AI Engineer Jobs

The AI Research Engineer will design and implement ML models, develop RL algorithms, and collaborate on integrating ML systems, enhancing AI experimentation.

Work directly with clients to design, build, and deploy end-to-end production software and AI solutions. Lead solution architecture across backend, frontend, data pipelines, and ML models; develop production-grade applications; engage stakeholders from engineers to executives; and contribute reusable frameworks and best practices.

Design behavioral specs, harnesses, and validation systems so AI agents implement reliable full-stack features. Build CI gates, structural tests, linting, knowledge bases, and end-to-end verification. Diagnose failures across spec, harness, and agent layers. Architect and operate production systems across cloud and on-prem environments for regulated energy deployments, prioritizing reliability, observability, and graceful degradation.

As an AI Research Engineer, you will work on developing AI video ad models, collaborating with teams, and contributing to research for publications.

Design and build fault-tolerant, distributed infrastructure for AI agents (memory, state, execution). Own architecture, deploy production services, create observability/eval tooling, collaborate on compliance workflows, improve performance and reliability, and mentor engineers.

Join AlphaSense as a Senior AI Engineer to develop scalable AI services for their search products, focusing on large language models and cloud deployment.

The Principal Software Engineer will lead architectural decisions, mentor engineers, optimize system performance and reliability, and drive technical direction for LangChain's observability and evaluations platform.

Build and maintain integrations and automations connecting CRM, Microsoft 365, e-signature, custodial/banking systems and reporting. Use LLMs (Claude) and automation tools to extract, process, and verify document-heavy workflows with human-in-the-loop review, monitoring, and auditability, within security and compliance frameworks. Partner across teams and help set AI/automation standards.

As an AI Engineer at Extend, you'll build advanced document processing infrastructures and AI product features, impacting customer operations significantly.

The Automations & AI Specialist will enhance customer support using AI tools, optimize workflows, and analyze data to improve efficiency in product support.

As a Senior AI Systems Performance Engineer, you will benchmark AI workloads, optimize Ethernet fabric performance, and troubleshoot system bottlenecks, focusing on delivering actionable insights across teams.

As a Senior Fullstack Software Engineer, you will design and build fullstack systems for AI agents, collaborating with engineering, product, and design teams while documenting findings and participating in technical discussions.

Develop and deploy machine learning solutions for autonomous truck applications: EDA, deep learning model development, embedded deployment, data ingestion/curation, analytics, visualization, technical leadership, and process improvement across manufacturing and business domains.

Design and develop machine learning systems for construction robots, including scalable infrastructure, computer vision models, and data analysis for performance improvement.

Design and build secure, production-grade infrastructure that enables agentic AI systems to interact with Strikes platforms. Develop authentication/authorization for agents, orchestration and runtime environments, IDE agents, enterprise knowledge connections, tiered autonomy safety mechanisms, and embed with teams to operationalize frontier AI tools while enforcing security and ownership.

As an AI Infrastructure Engineer, you will manage user-facing services, ensure system reliability, and improve infrastructure using automation tools such as Ansible and Terraform while collaborating with various stakeholders.

Embed with cross-functional teams to map high-value workflows, design automated agentic or deterministic solutions, build production tools and integrations, monitor performance, run evaluations after model changes, and continuously improve AI-driven workflows while communicating impact to stakeholders.

The role involves owning the infrastructure for training and deploying RL-based control systems in humanoid robots, enhancing speed, efficiency, and collaboration among teams.

The Principal Engineer will lead AI-driven productivity initiatives, develop a strategy for integrating AI in engineering workflows, and improve collaboration across teams. Responsibilities include executing projects, ensuring code quality, and setting success metrics.

Design, build, and operate agentic AI systems for Roku TV: prototype, architect, and deploy agents and copilots; implement RAG, tool/function-calling, orchestration, observability, evaluation, and safeguards; integrate agents with backend services and production pipelines; collaborate across teams to deliver scalable, reliable solutions.

As an AI Systems Engineer, you'll design production systems for Codex agents, improve reliability and performance, and collaborate closely with research to enhance model capabilities.

Develop CAD automation pipelines and collaborate with teams to optimize designs for micromachines, ensuring manufacturability and functionality.

Design and implement backend services for an AI-driven automation platform, focusing on LLM orchestration, API development, and system reliability.

Develop real-time Voice AI systems, mentor juniors, and collaborate with customers to optimize call intelligence and reduce latency.

Design and build applications using Python, manage component design, optimize performance, and collaborate with clients on innovative products.