Top AI Engineer Jobs

Design and implement systems software for high-performance GPU clusters. Debug complex distributed systems and own the systems lifecycle from design to production.

The AI Platform Engineer will build a firmwide AI Development Platform, focusing on scalable and secure solutions, implementing AI capabilities, and improving productivity across the organization.

As an ML Engineer Intern, you will build and deploy ML models, design scalable infrastructure, and collaborate with data science teams in a fast-paced environment.

As an ML Engineer, you'll build and deploy scalable ML systems, optimize models, and collaborate with teams to improve content across platforms.

As a Training Manager/Curriculum Developer, design and deliver training programs in Intelligence, Cyber, Data Science, and AI, collaborating with SMEs to create impactful curriculum.

As a Software Engineer focused on generative AI, you will design scalable AI services, optimize APIs, and collaborate with cross-functional teams to enhance enterprise-wide transformation.

As a System Engineer, you'll design, deploy, and maintain cloud systems for AI workloads, troubleshoot complex issues, and collaborate with teams to optimize performance.

Design and build backend systems for AI workflows, optimize solutions using Python, integrate AI/ML tools, and collaborate with teams for enterprise applications.

Design, develop, test, and deploy scalable software solutions and AI assistant capabilities. Integrate generative AI/LLM frameworks, vector databases, and cloud services. Collaborate across teams, provide technical guidance, mentor junior engineers, and apply prompt engineering and responsible-AI guardrails.

Lead design, build, and deploy scalable Generative AI and ML systems into production. Implement LLM integration, prompt engineering, RAG, conversational interfaces, model monitoring, evaluation frameworks, APIs, inference optimization, and collaborate to productionize forecasting and ML models.

Design, implement, and maintain RAG pipelines and LLM integrations, build embedding generation and retrieval systems, develop REST API integrations, and refine Postgres schemas to support tactical intelligence data workflows in onsite, mission-focused environments.

The Senior AI Platform Engineer will build and scale an AI procurement platform by developing backend services, integrating AI workflows, and creating user-friendly interfaces.

Build AI agents and architect product flows for NegotiateAI, focusing on agentic AI capabilities, user experience, and data handling requirements.

Evaluate AI-generated coding interactions, assess quality of engineering judgments, provide feedback, and define standards for AI coding agents. Comfortable making subjective judgments about engineering quality.

As a Senior Software Engineer, you will build and architect the AI infrastructure, focusing on agent orchestration and collaborating with cross-functional teams to enhance product features for a large user base.

Provide technical support to public sector and enterprise customers, troubleshoot complex issues, translate security/compliance needs (FedRAMP), automate tooling via scripting and AI, collaborate with engineering and product teams to resolve issues, improve processes, and provide on-call coverage.

The role involves developing full-stack features swiftly, utilizing AI tools for coding, managing front and backend systems, and ensuring production quality through testing and CI.

The Partner Solutions Architect will drive technical engagement with systems integrators, maintaining relationships with stakeholders to ensure successful AI solutions deployment and delivering strategic guidance.

Build and operate AI-native backend services that orchestrate multi-step, stateful LLM agents for GTM workflows. Design model-agnostic abstractions, integrate external systems, deploy containerized services on Kubernetes, ensure observability, and run experiments to measure effectiveness.

Develop a unified AI platform by designing and building scalable applications, improving platform performance, and collaborating with ML engineers.

Verify chip-level and performance behavior of custom ASICs: design end-to-end test flows with architecture team, run simulation-based verification, implement UVM environments, use constrained-random and functional-coverage methodologies, and coordinate vendors/contractors.

The role involves designing AI-driven workflows and automations, managing systems for enterprise integration, and collaborating across teams to implement scalable solutions.

As an AI Tools Engineer at Counterpart Health, you will evaluate and deploy AI-powered tools, optimize workflows, ensure security compliance, and promote tool adoption across teams.

The Data Engineer will develop and maintain AI context data capabilities, create data pipelines, ensure operational excellence, and follow compliance protocols. Responsibilities include data ingestion, retrieval quality improvements, and semantic layer implementation for AI integration within healthcare organizations.

Lead the development of AI systems for an automation platform, focusing on design, implementation, and evaluation of AI/ML projects in financial services.