Top AI Engineer Jobs

Design, build, and operate cloud-native data platforms and AI-powered applications. Implement ETL/ELT pipelines, transform structured and unstructured data, optimize data architectures for performance and scale, and collaborate with cross-functional teams to turn strategy into production solutions. Support operations, ensure data quality, and stay current with emerging AI and data technologies.

Design, prototype, and deploy AI-powered solutions by partnering with business stakeholders and engineering teams. Analyze processes, identify AI automation opportunities, build POCs/MVPs using LLMs and agents, define KPIs, document and train users, and drive adoption and scalability of reference AI solutions across the organization.

Design and prototype AI-driven solutions with business stakeholders, translate requirements between business and engineering, measure ROI and KPIs, document and train users, drive adoption of LLMs and AI agents, and mentor future AI practitioners to scale Citi's AI capabilities.

Partner with business and technology leaders to analyze processes, design and prototype AI/LLM-driven agent solutions (POCs/MVPs), measure KPIs, document and train users, drive adoption and scaling of reference solutions, and mentor future AI engineers to sustain enterprise AI capabilities.

Build and operate production-grade AI agent systems and connectors into governed data (Bronze layer). Design multi-agent workflows, enforce data contracts, implement observability, guardrails, cost controls, governance, and durable documentation while collaborating with stakeholders.

Design and build the LLM orchestration layer and multi-agent workflows that enable streaming chat, tool use, memory, function-calling, and autonomous reasoning; prototype agent behaviors; integrate LLMs with frontend/backend systems; evaluate frameworks for performance, safety, and extensibility.

Design, build, and test software for spacecraft and ground systems across the full stack. Develop flight and real-time control software, simulation and hardware-in-the-loop testing frameworks, integrate with hardware teams, support system bring-up and on-orbit operations, and create tooling for automation and mission operations in resource-constrained, high-reliability environments.

The Innovations and AI Solutions Engineer develops and optimizes AI solutions, manages data flows, implements machine learning models, and collaborates with users on data analysis and reporting.

As a .NET Developer (AI), you will design enterprise applications with AI capabilities, optimize agent behavior, and collaborate across teams to drive innovation in solutions.

As a Research Engineer, you will tackle AI safety challenges, develop evaluation methodologies, conduct adversarial testing, and work on model alignment and interpretability. You'll bridge theoretical and practical applications of AI safety research and collaborate with product teams to implement safety solutions.

Design, build, deploy, and maintain AI-integrated full-stack web applications, chatbots, and dashboards. Collaborate with ML and backend teams to ensure secure, scalable, high-availability production systems and monitor model outputs and training analytics.

The role involves automating software testing processes for vehicle systems, developing AI-assisted workflows, improving testing efficiency, and collaborating with engineering teams.

Manage model launches and provider onboarding in an AI marketplace, focusing on integration, QA, and internal tooling improvements.

As a Senior Full-Stack Software Engineer, you will design, build, and ship AI-powered systems to optimize workflows in the single family rental market, focusing on backend services and full-stack development in a fast-paced environment.

Design and implement .NET/C# features integrating AI services (agentic workflows, RAG, vector DBs). Improve performance, contribute to architecture, use source control, participate in code reviews, and collaborate cross-functionally to deploy scalable AI-enabled solutions.

Design, implement, and support AI/ML systems, working with business units to optimize workflows and educate staff. Communicate findings to stakeholders and ensure compliance with policies.

The Technical Solutions Engineer resolves customer issues, troubleshoots complex network environments, and collaborates with engineering teams to ensure customer satisfaction.

As a Senior Software Engineer, you'll build and deploy AI-powered solutions, collaborating with clients to optimize workflows, design systems, and handle ambiguous problems.

Design and implement an AI Copilot for ArcGIS Pro, focusing on AI models and natural language processing tools while collaborating with cross-functional teams to deliver high-performance software.

The AI Kernel Engineer will develop and optimize AI kernels for Quadric's platform, enhancing performance across various hardware configurations and providing technical support.

Build and scale backend infrastructure for Ambient AI in healthcare. Work across real-time clinical documentation, AI-driven billing automation, and clinical intelligence. Ship production systems, collaborate with clinicians and customers, maintain reliability, monitoring, and metrics, and operate across the full software stack.

The AI Observability Engineer monitors AI model performance, manages data quality, ensures compliance with Responsible AI principles, and collaborates on AI governance initiatives.

Lead QA for cloud-native AI/ML platforms: define test strategies, build and maintain automated test suites, validate data pipelines, models, and infrastructure (IaC), integrate tests into CI/CD, perform observability and non-functional testing, and collaborate with data scientists, engineers, and vendor teams to ensure reliability and scalability.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

The Staff Software Engineer will design and build AI platform systems, focusing on context management and model integration, driving infrastructure quality for legal applications.