Top AI Engineer Jobs

The Senior AI Engineer will build and scale AI features, develop AI agents, and partner with product teams to enhance products for small businesses.

As a Staff AI Engineer at Fieldguide, you will define technical direction, build AI systems, mentor engineers, and drive organizational leverage across various teams, while focusing on enterprise-grade reliability.

The role involves designing and building AI agents for audit workflows, owning product areas end-to-end, and mentoring other engineers.

As an AI Engineer at Fieldguide, you'll develop AI agents for complex audit workflows, design systems for reliability, and optimize agent capabilities based on customer needs. You'll build and integrate systems using LLMs and ensure agents improve over time, collaborating closely with product and design teams.

As an AI Engineer, you will create a unified evaluation infrastructure for AI agents, ensuring reliable performance while integrating automated pipelines and feedback systems for rapid model evaluation and quality assurance.

Lead design, deployment, and production scaling of LLM-based and agentic AI systems; evaluate and benchmark models; build prototypes and production AI pipelines; collaborate with engineering and business stakeholders; influence leadership and mentor junior team members.

Design, build, and scale production LLM, retrieval, and agentic AI systems for compliance automation. Implement evidence-grounded, explainable workflows, optimize for latency/cost/reliability, and embed human-in-the-loop guardrails while collaborating cross-functionally.

Build and deploy production-scale AI/LLM systems: own ML lifecycle from model development to serving, optimize GPU/Kubernetes deployments, design LLM applications and APIs with monitoring, apply CI/CD and version tracking, collaborate with product teams, and contribute to AI engineering best practices.

The Lead AI Engineer will develop and deploy AI components, optimize large language models, and improve AI systems performance while collaborating with cross-functional teams.

Lead the development and deployment of AI-powered products with a focus on foundational AI systems, LLM optimization, and team collaboration to enhance user experiences in banking.

As a Lead AI Engineer at Capital One, you will design and support AI software, develop LLM and optimization techniques, and collaborate with cross-functional teams to innovate AI products.

As a Senior Lead AI Engineer, you will design, develop, and optimize AI systems while collaborating with a cross-functional team to implement AI-driven products.

As a Senior AI Engineer at Klaviyo, you will design and build scalable backend systems and AI solutions, collaborating with product managers and engineers to enhance AI technologies for optimizing customer experiences.

As a Lead AI Engineer, you will design and develop AI components, collaborate across teams, improve performance, and contribute to Capital One's AI vision.

The Senior Lead AI Engineer will design and develop AI-driven products, enhance scalable AI systems, and collaborate with cross-functional teams.

Drive AI/ML initiatives across storage product development, coordinating engineering, firmware, validation, and data science teams from requirements through deployment. Manage schedules, dependencies, blockers, readiness reviews, portfolio progress, and Go/No-Go decisions. Align priorities with business goals, identify AI/ML opportunities, support adoption of AI-assisted tools, and communicate program status and outcomes to executives and cross-functional stakeholders.

Design, develop, and deploy AI-powered healthcare solutions using Java and Spring Boot microservices. Implement HL7 FHIR and Da Vinci interoperability standards across prior authorization, claims, eligibility, and provider domains. Build Kafka-based event-driven services, integrate relational databases, automate CI/CD, deploy with Docker and Kubernetes on AWS or Azure, and establish monitoring using Splunk, ELK, Prometheus, and Grafana.

Lead the design, development, and deployment of AI-powered healthcare solutions and Java/Spring Boot microservices. Build interoperable clinical platforms using HL7 FHIR and Da Vinci standards, event-driven Kafka components, relational databases, CI/CD pipelines, containers, cloud infrastructure, and observability tools. Address clinical workflows, prior authorization, claims, eligibility, and provider-data challenges while evaluating emerging technologies and promoting responsible AI use.

Leads hands-on development of AI and machine learning solutions for asset and wealth management. Designs scalable data pipelines, develops and productionizes ML and LLM models, builds inference services, and deploys solutions to AWS or Azure. The role includes end-to-end architecture, data analysis, real-time data processing, LLM workflow implementation, collaboration with business and technical partners, and leadership in generating innovative GenAI solutions.

Lead architecture and development of a firm-wide software dependency risk platform on AWS and Java. Own data ingestion, dependency graph modeling, APIs, integrations, technical strategy, and production delivery. Establish agentic AI engineering practices using tools such as Claude, with governance for security, resiliency, auditability, and human validation. Mentor senior engineers, solve complex technical problems, and represent engineering across security, risk, compliance, and platform stakeholders.

Lead design, build, and deploy production-scale generative AI and agentic systems: foundation model training, LLM inference, vector search, guardrails, evaluation, observability, and performance optimization across cloud infrastructure.

Design, build, and deploy scalable ML training and evaluation platforms for autonomous driving. Lead architecture and implementation of distributed, high-performance pipelines, drive cross-team prioritization, mentor engineers, and support recruiting and code quality to accelerate ML model development lifecycle.

Lead design and deployment of scalable ML platforms and tools, manage complex technical projects, mentor junior engineers, and collaborate across teams to enhance autonomous driving systems.

Build and deploy production AI agents for real customers. Responsibilities include orchestrating LLM pipelines, integrating APIs and tools, developing React interfaces, implementing RAG and document-processing systems, deploying serverless applications, and monitoring performance. The role requires strong Python or JavaScript skills, hands-on OpenAI and multimodal LLM experience, vector databases, agent frameworks, function calling, and full-stack integration. Applicants must be pursuing a Master's or PhD in a technical field.

Build the core AI intelligence layer for an energy infrastructure platform. Own technical strategy, architecture, production engineering, agentic workflows, data and geospatial pipelines, security, and observability. Translate energy procurement and project finance workflows into software, automate contracting and diligence, and iterate directly with users to achieve product-market fit. This founding role requires autonomous execution, rapid prototyping, technical leadership, mentorship, and comfort with startup ambiguity.