Top AI Engineer Jobs

The Staff Software Engineer will lead the development of cloud-native AI platforms, optimizing AI workload deployment in Kubernetes environments and collaborating with cross-functional teams.

Design, build, and deliver an AI and machine learning platform, enhancing developer velocity while collaborating with cross-functional teams.

Develop and optimize AI models and training systems for robotics applications, focusing on design, implementation, and performance optimization of ML models.

Support DoD Emerging Technology Mission Assurance by researching, evaluating, prototyping, and integrating AI/ML/Generative AI solutions. Design and run technology evaluations, PoCs, and lab tests; develop assessment reports, architecture, CONOPS, and migration roadmaps; evaluate model performance, scalability, security, and cloud integrations; brief stakeholders and support transitioning capabilities to operational environments.

Build and deploy AI/LLM-powered automations and API integrations to streamline back-office processes. Partner with cross-functional teams to gather requirements, design workflows with orchestration tools, write tested production code, measure automation impact, and stay current on AI tooling.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Embed with business teams to discover high-value AI opportunities, design and build agentic AI-enabled workflows and integrations, validate prototypes with users, iterate for production readiness, document risks and controls, and convert solutions into reusable patterns while collaborating with governance, security, and data partners.

As an AI Product Engineer, you will develop and deploy LLM-powered language learning products, enhance existing features, and collaborate cross-functionally to optimize performance and user experience.

Lead end-to-end AI-first transformation for operations: define problems, design architecture, build agentic systems and automation pipelines, integrate with CRMs and operational tooling, ship production solutions and drive company-wide AI adoption.

Own and ship backend systems and agentic AI features for telemetry analysis: design agent tool interfaces, build distributed job execution on Kubernetes, implement APIs and MCP server, integrate frontier models, and build evaluation and observability for production agent workloads.

Lead design, build, and operate backend agentic systems that analyze large-scale time-series telemetry. Own product from customer discovery through shipping. Implement APIs, distributed job execution on Kubernetes, sandboxed code execution, context/memory management, evaluation suites, and observability while integrating frontier models and scaling agent workloads.

Build and operate backend systems for agentic AI that analyze large-scale time-series telemetry. Own product features from customer discovery through deployment: APIs, distributed job execution on Kubernetes, sandboxed code execution, context management, observability, model integration, and evaluation suites.

Build and operate agentic backend systems that reason over large-scale time-series telemetry. Design APIs, tool interfaces, sandboxed code execution, distributed job scheduling on Kubernetes, observability, and evaluation suites. Partner with customers and product to turn real workflows into dependable AI agent capabilities across cloud and on-prem deployments.

As a Research Engineer, you will optimize AI performance, focusing on kernel development for large-scale ML workloads, profiling bottlenecks, and collaborating with teams to enhance model training and inference.

Lead design and delivery of ML, generative AI, and agentic AI solutions for finance use cases. Architect secure, scalable AWS-based systems, implement MLOps, CI/CD, observability, data/model pipelines, APIs, and production monitoring. Mentor engineers, collaborate with cross-functional stakeholders (risk, compliance, business), and ensure compliance, auditability, and cost controls for production AI systems.

Build and own full-stack features for core user journeys, shipping backend APIs, async workflows, and frontend experiences. Contribute to architecture, write well-tested maintainable code, partner with product and design, and proactively address technical debt and performance issues.

Design and build Renterra's data and AI foundation: event architecture, data pipelines, analytical systems, and ClickHouse-based queries. Create AI agents and intelligent workflows that use company data to solve customer problems. Ensure production reliability, observability, security, and measurement via evaluations and feedback loops. Partner across product, engineering, leadership, and customers; report to the CTO.

Build high-performance, scalable React+TypeScript web applications for payment experiences. Design reusable UI components and optimize frontend performance while collaborating with cross-functional teams on architecture, testing, accessibility, and product delivery.

Architect and implement a cross-platform design product across client apps, cloud services, and device connectivity. Champion AI-native engineering practices, drive end-to-end architecture and ADRs, ensure security/reliability/observability, own delivery and release health, and mentor engineering leaders while partnering cross-functionally across product, design, firmware, and security.

As a Staff ML Engineer, you'll lead complex model quality improvements in clinical AI, spanning research and engineering, optimizing performance under high compliance conditions.

Integrate LLMs, RAG, and agentic-AI into secure decision-support software. Design prompts and inference workflows, connect AI to backend services, evaluate outputs, build tests, document designs, and collaborate with engineering, security, and DevSecOps teams to deliver reliable mission-capable AI features.

As a Staff AI Research Engineer, you will develop AI solutions, implement machine learning algorithms, benchmark techniques, and transition prototypes to production.

Lead design, implement, and manage scalable AWS/Azure cloud infrastructure to support Generative AI. Collaborate with data scientists to deploy and optimize models, use Terraform for IaC, ensure security and performance, mentor engineers, troubleshoot deployments, and document best practices.

The Senior Systems Software Engineer will optimize AI stack readiness for the DGX Station, focusing on application performance, DL framework analysis, system-level optimization, and collaborating with cross-functional teams to enhance multi-GPU capabilities and ensure product effectiveness.

Design and deliver high-performance, area- and power-efficient ASIC/GPU micro-architecture and RTL. Develop agentic AI solutions to craft micro-architecture, implement RTL, and produce fully verified, synthesis/timing-clean designs. Collaborate with designers and tool owners, and build LLM-powered engineering assistants, multi-agent systems, and multi-modal dialogue tools to accelerate chip design workflows.