Top AI Engineer Jobs

As a Staff AI Engineer, you'll lead AI product development, overseeing technical direction, system deployment, and model evaluation while collaborating across teams.

Lead the development of AI software components for Capital One, including model training, inference, and system optimization. Collaborate with cross-functional teams to deliver groundbreaking AI solutions, ensuring quality and scalability while mentoring junior team members.

As a Distinguished AI Engineer, you will design and develop AI software, partner with cross-functional teams, and create optimized AI systems to enhance customer interaction and improve banking services.

As a Lead AI Engineer at Capital One, you will design and develop AI systems, collaborate with cross-functional teams, and optimize AI solutions for performance and scalability.

The role involves designing AI systems for mental healthcare, focusing on building scalable, production-grade systems that enhance patient engagement and clinical operations. Responsibilities include setting technical standards and ensuring safety and reliability while working with advanced AI technologies.

The Staff Product Manager will own the strategy for AI-enhanced developer tools, driving adoption, coordinating across teams, and defining success metrics for AI workflows in the automotive sector.

The role involves partnering with cross-functional teams to design, develop, and deploy AI software solutions, focusing on large language models and AI optimization techniques.

The role involves designing, developing, and optimizing AI software components, collaborating with cross-functional teams, and contributing to the technical vision of AI systems at Capital One.

The role involves designing, building, and maintaining an MLOps platform, developing workflows for ML applications, and integrating various technologies while supporting agile teams.

Lead design, build, deploy, and support scalable, responsible AI systems (foundation model training, LLM inference, similarity search, guardrails, observability). Collaborate with cross-functional teams, optimize model performance and cost, and shape technical vision and roadmap for foundational AI platform services.

Design, develop, and deploy Generative AI and ML solutions (LLMs, RAG, agentic frameworks) for healthcare claims adjudication. Build end-to-end pipelines, apply MLOps, ensure LLM security and responsible AI, deploy on cloud platforms, integrate data warehousing, collaborate with product and platform teams, and mentor junior engineers.

The Lead AI Engineer will design and implement LLM-powered applications, optimize RAG pipelines, and evaluate models while integrating AI systems into production environments.

The Senior Engineer collaborates with teams, designs and implements technical features, writes production-ready code, and ensures high-quality deliverables, while also engaging in research and learning on new technologies.

As an AI Engineer, you will build and scale AI business applications, focusing on generative AI. Responsibilities include rapid prototyping, applying software engineering best practices, and providing production support.

The Principal AI Engineer will lead the development of AI systems, manage agentic delivery tools, define KPIs, and mentor engineers while ensuring effective integration and adoption across teams.

The AI Engineer designs and deploys AI automation tools, partners with teams for workflow automation, and enhances operational efficiency using generative AI and data-driven decision support.

Lead hands-on engineering delivery of agentic AI solutions for GTM systems. Design and build LLM-powered workflows, autonomous agents, RAG and semantic search pipelines, Salesforce and Slack integrations, CI/CD and observability, enforce AI governance/security, mentor engineers, and drive prototypes to production across enterprise GTM platforms.

Lead embedded AI transformation by partnering with business units to design, build, and deploy production-grade AI assistants and multi-agent solutions, while training and mobilizing teams through hands-on engagement, playbooks, and scalable adoption frameworks that deliver measurable business outcomes.

Lead embedded AI transformation by partnering with business units to identify high-value opportunities, design and deploy production-ready AI assistants and multi-agent solutions, and coach teams to adopt AI-first practices. Build reusable playbooks, measure business outcomes, and scale capability through hands-on engagements, workshops, and train-the-trainer programs.

Embed with business units to identify and deliver production-ready AI assistants, agents, and orchestration frameworks. Lead discovery-to-deployment engagements, coach technical and non-technical teams, create reusable playbooks and reference architectures, and drive measurable adoption of AI-first workflows across the enterprise.

Lead embedded AI transformation by partnering with business units to identify high-value use cases, design and deploy production-grade AI agents and assistants, and train teams. Build repeatable architectures, playbooks, and training to scale AI adoption, measure business impact, and develop internal champions.

Embed with business units to identify high-value AI opportunities, design and deploy production-ready AI assistants and multi-agent systems, and coach teams to adopt AI-first workflows. Deliver reusable architectures, playbooks, and training while measuring adoption and business impact to scale capability across the organization.

Embed with business units to identify high-value AI use cases, design and deploy production-ready AI assistants and multi-agent solutions, and coach teams to adopt AI-first workflows. Deliver measurable business outcomes, create reusable playbooks and training, and scale organizational capability through hands-on engagements and knowledge capture.

Lead development and scaling of an enterprise AI platform: design tooling and frameworks, optimize GPU/CPU resources, build data pipelines, mentor engineers, enforce security and governance, and lead cross-functional AI initiatives to improve model performance and deployment.

Develop core platform services and automation using Python, assist with integrations, apply telemetry practices, maintain documentation, and support CI/CD processes.