Top AI Engineer Jobs

Build and scale an enterprise Knowledge Graph platform and semantic pipelines to power AI-driven features. Design graph models, semantic routers, vector/RAG workflows, cloud-native data pipelines, and AI developer tooling. Own feature delivery, ensure code quality, mentor engineers, and collaborate across product, ontology, and engineering teams.

Develop algorithms in machine learning and statistics to address complex challenges. Design data pipelines and deploy solutions using cloud infrastructure.

Lead a Labs team as a hands-on engineer building hybrid AI/optimization systems: design ML-augmented optimization, prototype and productionize solutions, architect MLOps/CI-CD, benchmark solvers, mentor engineers, and collaborate with researchers and stakeholders to scale reusable components and APIs across Kroger.

Lead architecture and implementation of Vumedi's AI discovery platform: design personalized recommendation systems, semantic search, retrieval and ranking pipelines, vector/embedding-based search, RAG/knowledge-graph integrations, scalable inference and retrieval services, and evaluate emerging AI technologies while partnering with product, data science, and engineering to deliver production LLM-powered discovery for physicians.

The role involves owning product areas, working on backend, frontend, and with LLMs/ML models, delivering high-quality experiments, and engaging customers.

The AI Platform Production Engineer will automate deployment and management of AI workloads, ensure system reliability, and enhance tooling for production services, leveraging extensive engineering expertise.

Manage and optimize cloud-based streaming platforms, ensuring high availability and performance for real-time analytics. Collaborate across teams to enhance data pipelines and integrate AI solutions.

Manage deployment, versioning, and lifecycle of AI models across multi-cloud platforms. Define reusable AI patterns (RAG, orchestration, prompts, vectors), build embedding and retrieval pipelines, establish CI/CD and IaC, ensure telemetry and governance, collaborate with security and vendors, and provide platform documentation, training, and technical leadership.

The role involves leading AI-augmented development practices, building AI/ML cybersecurity solutions, mentoring team members, and collaborating cross-functionally to enhance software delivery using advanced technologies.

As an SDK Software Engineer, you will develop and maintain AI SDKs, collaborate with teams, and contribute to open-source projects.

The role involves building AI platform capabilities, mentoring engineers, collaborating with teams, and scaling systems for large datasets as part of a legal tech transformation.

Lead data science work with clients: analyze structured and unstructured data, develop predictive models and NLP solutions, visualize results, integrate enterprise systems, and guide teammates to deploy AI/ML workflows that inform decisions.

Design and implement AI solutions for Marine Corps needs, develop algorithms, mentor team members, and create scalable data platforms. Requires collaboration in a team environment.

Design and build backend infrastructure for agentic AI products: orchestrate low-latency agent runtimes, scale RAG/vector search systems, develop large-scale evals and testing pipelines, productionize multi-tenant AI microservices with observability and cost/performance optimizations, and collaborate with modeling teams to deliver secure, scalable enterprise AI features.

Design and build safe, auditable agent and autoresearch infrastructure: closed-loop evaluation, isolation and permissioning, experiment orchestration, and large-scale inference/training pipelines. Enable autonomous research loops, evaluator and confidence machinery, and agent runtime features (orchestration, sandboxing, tool frameworks, memory, retrieval). Work end-to-end with engineers to deploy trustworthy LLM-agent capabilities against production systems.

Design, develop, and deploy AI/ML models and pipelines for chemical and biological threat characterization. Build data preprocessing, embedding, entity extraction, and model monitoring systems; integrate models into secure cloud environments via APIs and MCP. Create model cards, explainability tools, and support knowledge graphs. Ensure DoD cybersecurity compliance, participate in Agile teams, and assist knowledge transfer and documentation.

Develop and refine AI models and tools to improve customer service automation. Apply prompt engineering and fine-tuning, design AI systems for complex workflows, integrate solutions with cross-functional teams, and contribute to strategic AI initiatives that increase efficiency and customer satisfaction.

Build and maintain enterprise AI governance components (LLM gateway, Agent Firewall) across full stack (Go backend, React frontend). Ship features, harden security, integrate LLM provider APIs, collaborate with product, partners, and enterprise customers, and contribute to open-source tooling.

Lead full-stack product engineering for AI-powered healthcare features. Build frontend experiences, backend services, APIs, relational data models, and AI workflows. Prototype, ship, and iterate production systems; improve AI via evaluation and product signals. Ensure reliability, privacy, observability, and operational readiness while collaborating with product, design, customers, and engineers.

In this role, you will lead the AI engineering lifecycle for Snowflake Database Engineering products, enhancing workflows and collaborating to address customer needs.

Lead design and implementation of production agentic AI systems that integrate LLMs with Teak's platform APIs. Build RAG pipelines, MCP/tool integrations, evaluation frameworks, and AI infrastructure on cloud (AWS/GCP/Azure). Contribute backend services in Python, ensure compliance and safety, and operate systems in production including observability and on-call duties.

The AI Engineer will design and implement scalable AI systems, collaborate with stakeholders, and influence AI strategy to integrate AI solutions into business operations while ensuring compliance with regulations.

Build and ship end-to-end AI-first product features: extend a Neo4j Brand Knowledge Graph, design predictive optimization and measurement systems, implement LLM orchestration and integrations, develop React/TypeScript frontends and scalable backends, participate in client-facing demos, and own QA and documentation.

The Senior Staff Engineer will lead the development of an underwriting platform, enhance AI integration, mentor junior engineers, and collaborate with teams to transform GEICO's underwriting processes through tech innovations.

Design and ship end-to-end customer-facing AI experiences, focusing on data-dense, BI-quality frontends (React/TypeScript) while owning APIs and backend design. Build interactive, real-time, agent-driven workflows, manage complex client-side state, and collaborate across the stack to deliver polished production-grade financial analytics and book-close tools.