Top AI Engineer Jobs

Designs, deploys, and operates high-speed data center networks supporting AI clusters and Top Secret national security missions. Responsibilities include optical and copper connectivity, network automation, capacity planning, security, performance optimization, troubleshooting, hardware and firmware integration, and collaboration with ML and engineering teams. The role also mentors junior engineers, leads technical decisions, supports deployments, and participates in on-call rotations and travel.

Designs, deploys, operates, and scales GPU/CPU infrastructure supporting Top Secret national security missions. Responsibilities include managing bare-metal and virtualized platforms, Kubernetes and AI clusters, operating systems, databases, monitoring, distributed storage, automation, and high-availability services. The engineer collaborates with AI and software teams, improves service lifecycles and performance, and supports infrastructure deployments at massive scale.

Leads AI technology capability planning for Medical Affairs and Health Impact. Translates business needs into scalable solution options, evaluates build-versus-buy and enterprise platform approaches, maintains the integrated AI roadmap, identifies dependencies and risks, and coordinates with architects, engineering, security, privacy, compliance, and delivery teams. Provides independent technical guidance without requiring deep model development or data science expertise.

Develop and deploy computer vision AI/ML algorithms for remote sensing, automatic target recognition, and multimodal EO/SAR data fusion. Responsibilities include processing large datasets, researching supervised and unsupervised methods, training and optimizing deep learning models, deploying solutions to cloud environments, mentoring engineers, communicating technical concepts, and preparing documentation. The role requires an active TS/SCI clearance and expertise in Python-based machine learning frameworks.

Lead development and architectural evolution of an AI-powered code security scanner. Build secure user-facing applications, reporting dashboards, backend orchestration and scanning services, LLM integrations, vulnerability analysis workflows, authentication, authorization, and cloud-native solutions. Mentor engineers and drive platform modernization, scalability, automation, testing, and long-term enhancements for enterprise applications in regulated environments.

Lead the architecture and development of backend platforms and agentic AI systems. Design scalable distributed services, APIs, runtimes, orchestration, integrations, evaluation systems, and observability capabilities. Drive ambiguous initiatives from concept through production, ensure reliability and safety, collaborate with customers and product teams, and mentor engineers while remaining hands-on with coding and operations.

Design and architect scalable AI-powered software systems, make technical decisions, ship production code, optimize performance, and resolve technical roadblocks. Partner cross-functionally to deliver initiatives from concept through completion, champion AI-forward development workflows, and contribute to evolving platform and product architecture in a highly regulated healthcare environment.

Build and deliver customer-facing AI solutions for finance teams, including agents, workflows, applications, and LLM-based systems. Lead customer discovery, recommend transformation opportunities, translate business needs into technical solutions, and own projects from discovery through deployment. Evaluate AI system performance, collaborate with Product, R&D, and Customer Success, support change management, and identify reusable platform capabilities.

Design, deploy, optimize, and maintain advanced machine learning models for monetization applications. Translate AI research into scalable production systems, build data pipelines, improve model performance, collaborate with research, engineering, product, and design teams, and contribute to model monitoring, code reviews, and end-to-end problem ownership.

Develop and integrate cloud software, AI/ML capabilities, distributed analytics, and microservices on AWS and large-scale compute clusters. Responsibilities include requirements analysis, Java development, cloud deployment, testing, troubleshooting, RESTful services, Hadoop-based big-data processing, infrastructure as code, CI/CD, and Linux systems work. The role requires active TS/SCI clearance with polygraph and one approved cloud developer certification.

Develop and sustain cloud software for cyber intelligence and AI/ML capabilities. Responsibilities include requirements analysis, Java development, distributed systems, cloud deployment, software integration, testing, troubleshooting, analytics development, and technical documentation. The role uses AWS, Kubernetes, infrastructure-as-code, CI/CD, Hadoop technologies, Linux, microservices, LLMs, and RAG frameworks while supporting large-scale data processing and national security missions.

Develop and sustain cloud software for national security missions, including requirements analysis, integration, testing, validation, and issue resolution. Build AWS-based services and distributed systems using Java, Kubernetes, infrastructure-as-code, CI/CD, Linux, and microservices. Integrate AI/ML capabilities, LLMs, and RAG frameworks while supporting large-scale compute clusters, big-data technologies, RESTful services, and cloud security practices. The role requires active TS/SCI clearance with polygraph and collaboration in a mission-driven cyber intelligence environment.

Designs and implements AI-enabled workflows for cyber and intelligence missions, including LLM-based agents, multi-step automation, API and data-store integrations, and production deployments in classified environments. Collaborates with mission users, analysts, developers, and leadership to translate operational workflows into reliable, secure capabilities. Requires Python experience, TS/SCI clearance with polygraph, and relevant AI/ML or software engineering experience.

Leads the design and development of cloud-native platforms supporting generative AI agents. Responsibilities include building backend services, developer enablement tools, CI/CD pipelines, Kubernetes and multi-cloud infrastructure, platform security, observability, DORA metrics, and production engineering practices. The role requires mentoring, architectural leadership, cross-functional collaboration, and expertise in cloud-native systems, networking, infrastructure as code, and systems programming.

Design, develop, test, deploy, and maintain scalable AI/ML and full-stack software using Java and Python. Customize LLM interfaces, integrate external requirements tools, troubleshoot defects, conduct code reviews, support planning, design accessible user interfaces, and mentor junior engineers. The role requires collaboration with customers, product managers, developers, subject matter experts, and leadership in a classified Intelligence Community environment.

Build backend architecture and infrastructure for LLM-driven agent systems, including orchestration, tool integration, context management, evaluation, observability, and production deployment. Develop services connecting AI models with insurance data and platform APIs, define reliable AI-native architectural patterns, and collaborate with product, design, and engineering teams to deliver underwriting workflows.

Leads a three-person computer vision team developing, training, optimizing, and deploying custom YOLO object-detection models for live full-motion video. Architects secure data and training pipelines, establishes annotation standards, manages dataset challenges, and optimizes inference using GPU acceleration. Integrates computer vision systems with video and software platforms while coordinating Agile delivery, technical direction, metrics, and code standards. The role requires advanced Python, deep learning, video processing, model deployment, and team leadership experience.

Manages the enterprise AI portfolio and coordinates use-case intake, prioritization, governance, reporting, and value realization. Supports the design, integration, deployment, and secure adoption of AI and LLM solutions. Engineers and maintains cybersecurity tools, automations, and integrations while supporting vulnerability management, incident response, risk assessments, audits, policy development, and compliance activities.

Builds and ships user-facing product experiences and integrations using low-code, no-code, and AI-assisted development tools. Translates stakeholder needs into maintainable solutions, integrates platform services and APIs, applies authentication, security, privacy, and compliance controls, and partners with Product, Architecture, DevOps, Security, and QA. The role also defines testing, telemetry, documentation, runbooks, acceptance criteria, and post-launch product health metrics.

Build and deploy automation workflows, AI-enabled tools, and production-ready applications using LLM APIs and agentic frameworks. Translate business processes into scalable technical solutions, integrate enterprise systems and SaaS platforms, and collaborate with operators, analysts, leadership, and central IT. Provide training and documentation, support security and governance reviews, and contribute to shared AI development standards across business units.

Leads the architecture, development, deployment, and operation of enterprise AI Ops solutions, including RAG pipelines, agentic workflows, and AI-powered applications. Improves SRE practices, leads incident response, automates cloud infrastructure with Terraform and GitHub Actions, and ensures reliability, scalability, security, and responsible AI. Designs and operates software using Python and Node.js, manages Kubernetes environments, mentors engineers, and leads globally distributed technical teams.

Lead architecture, design, and delivery of Klaviyo's Customer Agent conversational AI platform. Drive technical strategy, build scalable AI-enabled features, establish observability and reliability practices, mentor engineers, and coordinate cross-functional initiatives to deliver production agentic systems for millions of users.

Lead architecture, design, and implementation of a scalable conversational AI platform (Customer Agent). Drive technical strategy for LLM-powered agentic systems, retrieval, orchestration, memory, evaluation, and reliability. Ship AI product features, establish observability/testing/operational best practices, lead cross-functional initiatives, mentor engineers, and evaluate emerging AI technologies to deliver reliable customer-facing experiences.

Design and implement algorithms for image processing and object tracking for spacecraft, integrating with flight software and conducting simulations.

The Principal AI/ML Engineer will lead the AV ML Infra team, overseeing scalable ML infrastructure, project ownership, collaboration, and team mentorship in AI and ML innovation at GM.