Top AI Engineer Jobs

As an AI Engineer, you will develop and optimize AI solutions, mentor team members, and collaborate on projects while ensuring system scalability and reliability.

The AVP DevX - AI Engineer/Technical Lead will design and implement cloud-native platforms, AI/GenAI solutions, and enhance developer workflows while collaborating with cross-functional teams to improve software delivery outcomes.

Design, train, test, deploy, and maintain AI/ML models and agentic workflows. Build AI-enabled applications (LLMs, RAG), secure cloud data foundations, event-driven integrations, and MLOps/DevSecOps pipelines. Collaborate with engineers, data scientists, architects, and product owners to deliver mission-critical solutions for the Air Force.

Design, train, test, deploy, and maintain AI models (LLMs, RAG, agentic workflows). Build secure cloud data foundations, implement MLOps/DevSecOps, design event-driven integrations, and collaborate with engineers and product owners to deliver mission-critical solutions for the Air Force.

Design, train, test, deploy, and maintain machine learning models and AI agents for mission-critical defense applications. Define ML strategy, apply best-fit algorithms, implement embedding/semantic search and RAG architectures, and collaborate with data engineers and product owners while ensuring AI safety, evaluation, and responsible practices.

Design, train, test, deploy, and maintain AI/ML models (LLMs, RAG, agentic workflows). Build AI-enabled applications and secure data foundations on cloud (AWS). Implement MLOps/DevSecOps, event-driven integrations, and collaborate with engineers, architects, and product owners to deliver mission-focused Air Force solutions. Secret clearance required.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Lead the development of AI systems integrating computer vision and language understanding, focusing on reinforcement learning and multimodal AI architectures.

The Senior Forward Deployed AI Engineer will create, deploy, and maintain AI systems, optimize workflows, and communicate with customers to address needs within production environments.

The Associate AI Engineer will collaborate with teams to design, build, and deploy AI solutions that enhance business processes and efficiency, using advanced AI technologies.

The AI Engineer will develop and deploy AI initiatives, ensuring high-quality execution and client satisfaction while collaborating with cross-functional teams.

The role involves designing and implementing AI features to enhance digital commerce experiences, collaborating across departments, and ensuring the quality and reliability of integrated AI services and workflows.

Lead architecture and development of a scalable, real-time Platform Chat product using LLMs and agent frameworks. Build orchestration layers, workflow automation, LLM integrations, and systems for observability, safety, and performance while mentoring engineers and collaborating with product and data science teams.

Build production-ready intelligent automations and agentic AI solutions. Full-stack development using TypeScript or Python, LangChain, vector DBs, RAG, and tool-calling. Collaborate with clients, ensure maintainable, tested, scalable deployments, CI/CD, observability, and model fine-tuning or deployment.

Design, build, and maintain scalable full-stack applications with cloud-native microservices and REST APIs. Integrate AI capabilities (LLMs, RAG, agentic workflows), ensure performance, observability, and reliability, own the full SDLC, and partner with stakeholders to deliver resilient, production-grade solutions.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

Design, build, and maintain customer-facing digital commerce services (checkout, billing, subscriptions, catalog, cart, orders). Use AI-assisted workflows for coding, testing, review, and documentation. Develop scalable, low-latency APIs and services, improve observability, automation, and engineering practices, and partner with cross-functional teams to deliver reliable solutions.

Lead design and evolution of customer-facing digital commerce systems (checkout, billing, payments, subscriptions, catalog, cart, orders). Use AI-assisted workflows to accelerate coding, review, testing, and documentation while ensuring security and production readiness. Drive architecture and API decisions across modern web apps, improve engineering excellence (testing, automation, observability, DevOps), build reusable patterns, and coach engineers to raise team productivity and technical delivery.

Lead design and delivery of AI-powered agentic architectures and automation across the studio pipeline. Build production-ready AI tools, prototype solutions for asset/tagging/queue management, integrate LLMs and DCC tools, define standards, monitor model drift and system reliability, produce reusable components, drive cross-team adoption, and measure automation impact while partnering with platform, security, and creative teams.

The Principal Engineer, AI/ML Architecture will define the technical direction for Coupa's AI platform, focusing on model training, evaluation, safety standards, and mentoring a team of ML and data engineers.

Build and ship AI-native workflows and prototypes for finance/accounting use cases, process large unstructured datasets, iterate with customer feedback, and design analytics-driven evaluation systems to improve product stability and value.

Design and implement foundational data systems for AI, focusing on efficiency and performance at scale. Collaborate on systems that optimize data handling and contribute to research advancements.

The Senior Staff Software Engineer will lead the architecture and implementation of AI-powered developer tools and workflows in a cloud environment. Responsibilities include mentoring, driving innovation, managing project delivery, and fostering a culture of continuous improvement.

The Lead AI Product Engineer will design, build, and operate AI agent systems, focusing on architecture, reliability, and performance while collaborating on user-centric workflows.