Top AI Engineer Jobs

Design and implement LLM‑powered and agentic workflows for intelligence missions. Capture user workflows, integrate AI with APIs and enterprise data, ensure production reliability and security in classified environments, and collaborate with operators and mission leadership to deliver AI-enabled decision support.

Design, build, and deploy AI-powered internal tools and intelligent workflows to automate People, Finance, Recruiting, and operations. Identify improvement opportunities, translate business needs into technical solutions, own end-to-end execution, and collaborate across teams to ship reliable production software and AI integrations.

Design, build, and ship AI-powered internal tools and intelligent workflows to automate operations across People, Finance, Recruiting, and other teams. Own end-to-end execution from discovery to production, integrate AI services, work cross-functionally, and iterate on deployed systems.

Design and build AI-powered internal tools and automations to improve operations across People, Finance, Recruiting, and business workflows. Own end-to-end delivery from discovery to production, integrating APIs, databases, cloud infrastructure, and AI systems while collaborating with cross-functional teams.

Design and optimize a low-level AI inference serving stack: customize open-source frameworks, build model partitioning/scheduling, integrate with proprietary accelerators, profile and optimize across Python orchestration to C++ kernels and drivers, and enable PyTorch-native deployment tooling.

Design and implement a novel AI inference engine through hardware-software co-design. Collaborate with ML, software, and cloud engineers; model PPA trade-offs; contribute to RTL design, simulation, verification, and roadmap planning to optimize inference for modern LLM workloads.

Lead design and implementation of cloud-first, AI-integrated full-stack applications on GCP. Drive rapid prototyping and MVPs, mentor developers, define architecture, maintain CI/CD pipelines, and collaborate cross-functionally to deliver production-ready solutions.

Design, operate, and evolve ElastixAI's Kubernetes and multi-cloud inference infrastructure. Run accelerated ML workloads at scale, build deployment and automation tooling, harden AWS/GCP/on-prem systems, partner with ML/runtime teams to productionize models, optimize costs and reliability, and participate in on-call rotation.

Design and implement IR transformations, graph optimizations, kernel lowering, and code generation for novel hardware. Decompose LLM/transformer workloads into primitives, build performance models and profiling tools, collaborate with ML and hardware teams, prototype end-to-end improvements from framework passes to custom kernels, and shape system architecture for an inference engine.

The Senior Software Engineer will develop AI/ML systems for debugging in production environments, integrating predictive analytics and issue resolution tools.

The AI Behavior Engineer will measure and shape AI model behaviors, collaborating with stakeholders to conduct evaluations and adapt methods for various contexts.

The AI Research Engineer designs and optimizes AI systems for enterprise automation, collaborating across teams to improve efficiency and decision-making.

Responsible for architecting AIOS solutions, leading proof-of-concepts, collaborating with engineering teams, defining roadmaps, and delivering project requirements.

As a Senior AI Kernel Engineer, you will design and optimize high-performance kernels for AI inference on GPUs and custom accelerators, improving performance and collaborating with various teams to influence architecture and implementation.

Design and implement high-performance, scalable inference systems for LLMs and VLMs across cloud, edge, and hybrid platforms. Develop and optimize custom kernels for hardware accelerators (GPU/NPU/DSP), integrate tensor/model parallelism, caching, and quantization, and collaborate with system and hardware teams to deploy production-grade AI inference.

The Staff Software Engineer will architect and scale backend systems for AI workflows, ensuring robust performance and reliability in enterprise applications.

Design and develop AI software for autonomous robotics, focusing on computer vision and VLA models, while collaborating across functions.

Design and build AI-driven agents and large-scale backend systems to improve efficiency in revenue organizations, ensuring reliability and scalability during high-volume processing.

Design and build scalable, event-driven backend systems for AI agents, ensuring reliable agent logic, orchestration, and fault tolerance across workflows.

Lead design, build, and operation of GenAI product features and a shared AI platform: RAG pipelines, LLM-driven personalization, conversational agents, agentic workflows, eval frameworks, and MLOps. Own end-to-end production lifecycle, observability, on-call, and integrations with marketing/BI systems. Collaborate with personalization teams and document architectural and evaluation outcomes.

Lead end-to-end technical strategy and implementation for iHerb's AI Platform and GenAI products. Design and build shared AI infrastructure (RAG pipelines, vector search, embeddings, evals, MLOps), set architecture and quality standards, deliver production AI systems, coordinate cross-team technical efforts, and mentor senior engineers.

Lead end-to-end enterprise AI solutions for an LLM-powered coaching platform: design, implement, and evaluate prompts, memory/knowledge patterns, and coaching flows; architect reusable components; define evaluation/guardrails; collaborate with Product and AI Engineering; mentor colleagues and measure deployment outcomes.

Design, implement, test, and maintain scalable C++ software for autonomous vehicle and perception systems. Work across full SDLC, support vehicle testing, simulation-based regression, data acquisition/analysis from remote vehicles, root-cause analysis, and mentor engineers while collaborating with ML researchers and cross-functional teams.

Lead design, prototyping, and operationalization of AI/ML and LLM-enabled capabilities for intelligence workflows. Collaborate with stakeholders to deliver production-ready systems, shape technical strategy, and automate mission analysis using scalable software architectures.

Design, build, and maintain end-to-end integrations between Commures platform and third-party healthcare systems (EHRs/EMRs). Implement scalable, reliable solutions using LLMs and modern cloud tooling, ensure HL7/FHIR and HIPAA compliance, troubleshoot production issues, mentor junior engineers, and drive integration platform architecture and monitoring.