Top AI Engineer Jobs

Lead design, build, and operation of production AI systems and inference stacks (vLLM) across AI Factory platforms. Implement RAG, MLOps, storage/networking, Kubernetes/containers, monitoring, security, and on-call incident response. Mentor engineers, engage clients, author runbooks, and contribute reusable patterns and tooling.

The Applied AI Engineer will architect, implement, and maintain AI agents for Edison's platform, collaborating with science and engineering teams and gathering insights from R&D partners to improve the agents' capabilities and reliability.

As a Forward Deployed AI Engineer, you will integrate Latent Labs' AI models with pharmaceutical clients' workflows, focusing on tech deployment, customer advocacy, and collaborative feedback for product improvement.

The AI Engineer will design, develop, and deploy AI-powered systems, improve operations with intelligent workflows, and collaborate on high-leverage AI opportunities.

Design, develop, and maintain secure MCP Servers for AI integration, ensuring scalability and system security while managing API integrations and tools for AI assistants.

As a Senior AI Engineer, you'll develop and deploy innovative AI solutions for the fashion industry, collaborate with cross-functional teams, and refine machine learning models to enhance product offerings.

As an AI Engineer, you'll lead backend implementation, build AI-powered products, and ensure high-quality systems, contributing to Elicit’s tech stack and user experience.

Design, architect, and scale cloud backend infrastructure for real-time media and sensor data streaming. Own reliability and throughput SLAs, collaborate with AI teams, and mentor engineers.

Responsible for designing and delivering multi-agent systems for AI products, collaborating with data scientists and offshore teams, and writing production-grade Python code.

As a Senior AI Engineer, you will design and implement AI solutions, collaborate with teams to define success metrics, and iterate on AI model performance.

Build the product harness for an Audit Agent: design backend systems, data contracts, APIs, and feedback/evaluation loops; ship customer-facing features; run experiments; and collaborate with frontend, agent, and customers to improve workflows and trust.

Lead frontend architecture and development for an AI-powered voice platform. Build responsive dashboards and reusable components, integrate real-time WebSocket and WebRTC voice capabilities, consume AI backend APIs, manage complex application state, and optimize performance, accessibility, and reliability. Mentor frontend developers, establish coding standards, collaborate with designers and backend teams, and develop prototypes, testing strategies, and production-ready interfaces.

Build LLM-based applications and agentic coding solutions to automate healthcare workflows. Work with non-technical stakeholders to design, deploy, monitor, and iterate production AI systems while ensuring security, privacy, and cost management.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

Founding data hire who builds end-to-end pipelines and models to convert messy enterprise data into AI-ready assets, defines data packs and ontologies, and builds internal tooling and automation so work compounds across customers. Works embedded with customer teams, partners with product and AI engineers, and makes architectural decisions about storage, orchestration, and data models.

Design, build, and ship production-grade LLM-powered and agentic AI solutions (RAG, retrieval pipelines, tool use) integrated into enterprise systems. Ensure code quality, observability, evaluation, instrumentation, and handover while collaborating with stakeholders and contributing reusable patterns and reference implementations.

Design, build, and ship production-grade LLM/agentic AI solutions (RAG, tool-augmented agents, retrieval pipelines). Integrate AI into enterprise systems, ensure observability and guardrails, maintain high code quality, instrument outcomes, and enable handover and reuse.

Lead a lean Innovation Office to design, build, and ship AI/LLM-powered MVPs that solve real insurance distribution problems. Hands-on role: write and deploy prototypes, integrate data science outputs, run discovery with agents, measure business impact, and hand off validated winners. Manage two data scientists and direct contract engineers while partnering with business leadership to prioritize and evaluate opportunities.

Design, build, and operate autonomous infrastructure AI agents on Airwallex's Quartermaster platform to automate SRE, DevOps, and DBA workflows. Integrate agents with Kubernetes, Terraform, cloud APIs, monitoring, databases, and CI/CD. Define agent architecture, safety guardrails, evaluation metrics, and collaborate with SRE and platform teams to deploy reliable, auditable autonomous systems in production.

Software Engineers will build AI agents for LiveFlow, focusing on designing integrated agent-driven systems to enhance financial software operations while ensuring data security and compliance.

Lead design, implementation, and optimization of Google Workspace and Microsoft 365 in enterprise and FedRAMP environments. Drive AI collaboration platforms (Gemini, Claude), deploy MCP servers and Agent Executor frameworks, automate user/group provisioning, manage IAM/RBAC and Jump host security, support ConMon and FedRAMP audit readiness, and integrate collaboration tools like Zoom and Lucid.

Build and maintain AI platform infrastructure, connectors, API integrations, and custom AI-powered applications. Implement authentication, data pipelines, and tooling to embed LLM capabilities across teams. Contribute code, documentation, reviews, and enablement while ensuring security and compliance for government requirements.

Build and lead an enterprise AI platform: design infrastructure, integrations, and custom AI applications. Own provider/tool selection, deploy production model pipelines and connectors, ensure compliance with government security requirements, mentor engineers, and deliver company-wide AI enablement and training.

Build and operate an enterprise AI platform and integrations that connect LLMs to internal systems. Develop production AI applications, manage model/provider evaluations, ensure security/compliance for government environments, and deliver company-wide AI training and enablement.

Develop and enhance AI Gateway platform, contributing to the design and maintenance of features for optimal reliability in AI workloads while collaborating with cross-functional teams.