Top AI Engineer Jobs

The Staff AI/ML Engineer will design and implement scalable ML infrastructure solutions, lead projects, mentor peers, and enhance ML productivity at GM.

Work with enterprise customers to identify problems, design and ship LLM-powered and agentic systems to production. Build context-learning capabilities, knowledge-management agents, evaluation and confidence systems, and scalable AI orchestration to drive adoption and expand impact.

In this role, you will lead the AI engineering lifecycle for Snowflake Database Engineering products, enhancing workflows and collaborating to address customer needs.

Lead design and implementation of production agentic AI systems that integrate LLMs with Teak's platform APIs. Build RAG pipelines, MCP/tool integrations, evaluation frameworks, and AI infrastructure on cloud (AWS/GCP/Azure). Contribute backend services in Python, ensure compliance and safety, and operate systems in production including observability and on-call duties.

The AI Engineer will design and implement scalable AI systems, collaborate with stakeholders, and influence AI strategy to integrate AI solutions into business operations while ensuring compliance with regulations.

Build and ship end-to-end AI-first product features: extend a Neo4j Brand Knowledge Graph, design predictive optimization and measurement systems, implement LLM orchestration and integrations, develop React/TypeScript frontends and scalable backends, participate in client-facing demos, and own QA and documentation.

Design and ship end-to-end customer-facing AI experiences, focusing on data-dense, BI-quality frontends (React/TypeScript) while owning APIs and backend design. Build interactive, real-time, agent-driven workflows, manage complex client-side state, and collaborate across the stack to deliver polished production-grade financial analytics and book-close tools.

As a Staff Backend AI Engineer, you will design and operate backend AI systems for Arbiter's care orchestration platform, ensuring reliability, low latency, and scalability while collaborating across teams and mentoring junior engineers.

Design and build autonomous AI agents that navigate websites and execute complex workflows using browser automation and LLMs. Integrate agents with APIs, SaaS, and internal systems, improve reliability through testing and guardrails, optimize performance and costs, and collaborate with product and engineering teams.

Join a team to develop AI tools for financial markets, focusing on building workflows and integrations, improving processes, and ensuring compliance.

Senior AI Engineer to design, develop, and productionize machine learning and AI systems for proprietary trading. Collaborate with researchers and traders to implement, optimize, deploy, and monitor models and scalable infrastructure, and contribute to technical direction and mentoring.

Lead design, deployment, and monitoring of LLM-based AI solutions. Build end-to-end generative AI applications, fine-tune models, integrate LLM APIs into products, ensure post-deployment performance, and collaborate cross-functionally within an Agile environment to drive measurable business impact in healthcare.

The AI Engineer will prototype AI solutions, advise on integration, manage AI initiatives, and collaborate across technology teams, ensuring alignment with business needs. Roles include monitoring AI trends, engaging stakeholders, and conducting knowledge-sharing sessions on best practices.

Architect, build, and deploy enterprise-grade full stack applications with React front ends and scalable back ends. Use AI-assisted tools and agentic workflows to rapidly prototype and iterate, ensure secure public-facing production readiness, implement authentication/authorization and cloud-based architectures, and partner with stakeholders to evolve prototypes into production systems.

Design, build, and ship AI-powered observability features using LLMs and agentic workflows. Rapidly prototype, iterate with real users, integrate AI into alerting, runbooks, and developer workflows, and ensure solutions are scalable, maintainable, and production-ready while collaborating cross-functionally.

Own and build production-grade integrations between Brex and external AI assistant ecosystems (OpenAI, Claude, Slack, etc.). Design secure, auditable patterns for data access and permissions, operate resilient integrations, define UX/reliability standards, and evangelize reusable AI capabilities across the platform. Partner cross-functionally to ensure safety, trust, and customer reliance.

Build the product harness for an Audit Agent: design backend systems, data contracts, APIs, and feedback/evaluation loops; ship customer-facing features; run experiments; and collaborate with frontend, agent, and customers to improve workflows and trust.

Own and build production-grade integrations between Brex and external AI assistant ecosystems (OpenAI, Claude, Slack, etc.). Define secure, auditable patterns for data/actions, permissions, and UX standards. Ship resilient integrations, partner cross-functionally, and create reusable AI capabilities and standards for external and internal use.

Design, develop, and maintain scalable CPQ solutions on Salesforce. Implement Apex and Lightning components, optimize existing systems, and mentor junior developers.

As a Senior Embodied AI Engineer, you will design and deploy intelligent control systems, manage simulations, and apply machine learning methodologies to enhance robotic performance in manufacturing environments.

The Sr AI Engineer designs and develops AI solutions to optimize business operations, integrating machine learning capabilities to enhance decision making and automation across functions such as supply chain and finance.

Lead design, build, and operation of production AI systems and inference stacks (vLLM) across AI Factory platforms. Implement RAG, MLOps, storage/networking, Kubernetes/containers, monitoring, security, and on-call incident response. Mentor engineers, engage clients, author runbooks, and contribute reusable patterns and tooling.

Responsible for designing and delivering multi-agent systems for AI products, collaborating with data scientists and offshore teams, and writing production-grade Python code.

The AI Engineer will develop AI tooling to enhance internal processes, collaborate on automation opportunities, and maintain AI systems to improve productivity.

The Lead AI Engineer will develop AI and ML systems with a focus on intelligent decision-making and data pipelines to improve agent performance and continuous learning.