Top AI Engineer Jobs

Lead the development of AI compiler tools, enhance performance analysis, collaborate with hardware teams, and mentor engineers to improve compiler tooling.

The AI Marketing Ops Consultant builds AI-powered marketing automation and workflows, integrates tools, documents processes, and collaborates with teams to optimize marketing operations.

The Principal Machine Learning Engineer leads the deployment of multi-modal AI models on mobile platforms, setting technical vision and optimizing inference performance, while mentoring a team and collaborating cross-functionally.

Lead engineering of the full embodied systems stack for real-world robots, owning onboard inference, data collection, teleoperation, and on-robot RL systems. Set architecture and technical direction, deliver reliable real-time deployments, close the loop between data, models and actions, and mentor engineers to scale embodied AI in industrial environments.

Lead and manage SAP ERP and procurement systems while developing AI-powered analytics, agents, and modern dashboards. Ensure integrations, data integrity, and adoption of global ERP initiatives. Build Python-based applications, implement RAG solutions, develop SQL data pipelines and REST APIs, and partner with stakeholders to deliver scalable automation and reporting.

Design, develop, and deploy end-to-end GenAI/LLM solutions on AWS. Build cloud-native, containerized systems (ECS/EKS/Docker/Kubernetes), support production geospatial applications, ensure security/compliance, and deliver production-ready architectures in collaboration with clients and teams.

Implement, administer, and support Microsoft 365, Purview, and Copilot services, focusing on compliance (DLP, sensitivity labels, eDiscovery, audit, insider risk), Copilot/AI administration, incident and problem management, operational resilience, and collaboration with security, architects, and business stakeholders.

Lead architecture and build AI-native developer tooling and autonomous agent systems to accelerate engineering workflows. Drive platform standards for reliability, safety, observability, and cost-efficiency while partnering across teams and mentoring senior engineers.

Lead design and implementation of AI-first testing frameworks and automation to validate LLM integrations and agentic Product Led Growth workflows. Perform white-box testing, identify and fix quality gaps, implement human-in-the-loop model evaluation, and collaborate cross-functionally to integrate quality across the agile delivery lifecycle.

Design, build, and optimize Azure cloud-native applications using .NET/C#. Implement serverless, distributed architectures, data pipelines, and CI/CD. Leverage AI-assisted development tools, apply TDD and automated testing, mentor engineers, participate in architecture and DevOps, and ensure performance, security, and compliance.

Lead design and build of AI-powered observability and AIOps platforms: agentic AI agents, predictive insights, automated remediation, integrations with observability tools, developer-first tooling, cloud-native scalable services, and end-to-end automation across hybrid environments. Serve as technical lead, define enterprise architecture, drive CI/CD and IaC practices, mentor engineers, and collaborate with cross-functional teams to improve reliability and incident response.

Design, develop, test, deploy, maintain, and enhance large-scale software solutions. Provide technical leadership and manage project priorities. Fine-tune foundation models and build adapters (Llama Factory, PEFT). Apply RAG techniques to populate and query vector databases (Weaviate). Build custom applications using LLM frameworks such as LangChain and DSPy.

Design, build, and optimize Azure-based, cloud-native .NET applications and services. Implement serverless, event-driven architectures, CI/CD, TDD, and AI-augmented development. Mentor engineers, participate in architecture and code reviews, and collaborate across Product, QA, and DevOps to deliver secure, scalable healthcare solutions.

Architect and implement low-latency sensor-to-GPU data pipelines, develop system software, drivers, and APIs, work across FPGA, networking, and CUDA stacks, integrate diverse sensors into Holoscan, and debug and optimize real-time distributed systems under strict latency and throughput constraints while collaborating with hardware, firmware, and AI teams.

The Software Engineer III - Voice AI develops and maintains the Voice AI platform for patient calls, optimizing real-time conversational AI features and mentoring team members.

Design and manage the voice AI architecture, developing multi-agent systems and real-time audio pipelines to enhance patient interactions and outcomes in healthcare.

Partner with frontier AI labs to translate research needs into evaluation frameworks, prototype pipelines and tooling, run experiments, mentor engineers, and establish repeatable patterns for large-scale post-training and benchmarking efforts.

Design and implement scalable enterprise data and lakehouse architectures; build and optimize cloud-based ETL/ELT and streaming pipelines for high-volume telematics/IoT data; integrate enterprise systems (ERP, CRM, service/warranty); prepare and enrich data for analytics, predictive maintenance, and AI/RAG applications; collaborate on governance, security, observability, and DataOps practices.

Design, build, and operate an enterprise AI platform: automate provisioning with IaC, deploy zero-downtime cloud services, enforce security and observability, review code, mentor engineers, and participate in 24/7 on-call rotation.

The Lead AI Forward Engineer designs AI solutions, guiding implementations for scalability and compliance, while mentoring teams and shaping technology strategy.

Lead design and delivery of end-to-end vertical AI products (financial services, science, healthcare, enterprise). Partner with research to productionize models, engage enterprise customers, set technical direction, mentor engineers, and drive cross-team product development from 0→1 and through growth.

The Internal Systems Engineer builds AI-powered tools and maintains a shared agent platform while integrating AI into customer operations at impact.com.

Lead AI&T for a Suit Mass Simulator: plan, coordinate, and execute hardware assembly, integration, verification, and flight test support. Manage interfaces, develop AI&T plans and procedures, track risks/anomalies, support readiness reviews and in-flight technical operations, and coordinate across disciplines to ensure NASA-JSC flight hardware standards and mission objectives are met.

Lead design, development, and deployment of scalable AI/ML applications and MLOps pipelines on Kubernetes. Mentor engineers, define best practices, adopt emerging GenAI tools, ensure observability, security, and alignment with business objectives, and maintain documentation and runbooks.

Drive architecture and implementation of an internal AI/agent platform: design agent runtimes and SDKs, define eval-driven release gates, safety, telemetry, and AuthX, partner with product teams to integrate reusable capabilities, set standards for prompt management and observability, write and ship production code, and mentor engineers.