Top AI Engineer Jobs

Serve as the senior client-facing technical lead to design and build data-generation, labeling, and evaluation pipelines for LLMs. Partner with executive stakeholders, diagnose data needs, architect multi-stage automated solutions (RAG, agentic workflows, synthetic data), run experiments, deliver production-ready pipelines, mentor engineers, and own delivery timelines and commercial outcomes.

As Lead ML Engineer, you will architect and build a conversational AI interface, optimize models for deployment, and collaborate with a multidisciplinary team.

As a Senior ML/AI Engineer, you will design and deploy a conversational interface, focusing on ML applications, latency optimization, and user experiences.

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.

The Lead AI Software Engineer designs and implements AI/ML solutions in healthcare, leading initiatives from model development to deployment while ensuring compliance and performance.

Lead design and delivery of high-priority AI initiatives across product and platform boundaries. Rapidly prototype and launch AI features, unblock teams, mentor engineers, and shape production-grade LLM systems (retrieval, evals, prompting, orchestration). Collaborate with product, design, and domain experts to turn customer needs into shipped product.

Lead design and implementation of AI-native test & measurement software, prototype AI-enabled features, solve critical technical challenges across the stack, champion CI/CD/DevOps/IaC, and align teams to productionize AI capabilities for scientific and engineering workflows.

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.

Design, develop, and deploy scalable cloud-native applications on GCP; integrate AI tools to automate business processes; collaborate with Agile teams and stakeholders to define requirements; improve systems, processes, and automation; maintain secure cloud development practices and stay current with cloud and AI trends.

Drive customer success for AI observability by architecting and delivering proofs-of-value, building integrations (data pipelines and ML infra), advising on model monitoring and governance, and championing customer needs across product, engineering, and sales to drive adoption and expansion.

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.

The Software Engineer will develop and enhance infrastructure and user-facing functionalities in cloud-native simulation platforms, collaborate on technical projects, and support AI and backend system initiatives.

Design and implement automation for ML integration and cyber incident response: data ingestion pipelines, malware analysis automation, LLM/Databricks/Bedrock integrations, API and data integration automation, feature engineering, monitoring, scaling to production, and documentation.

Develop and implement automation for ML/LLM integrations and data pipelines to support incident response and automated malware analysis. Build ingestion, transformation, monitoring, API integrations, and scale automation from pilot to production while ensuring data quality and documenting solutions.

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.

The Data Engineer will develop and optimize data pipelines for LLMs, ensuring high-quality healthcare datasets while collaborating with data scientists on model requirements.

Lead design and ownership of an AI-native web platform: web framework, design system, CMS, CI/CD, infrastructure, rendering and edge delivery. Define architecture and agentic SDLC, build evaluation guardrails, mentor engineers, and drive platform-wide technical alignment and migrations.

Build and scale web platform infrastructure (CI/CD, deployment automation, secrets management, edge delivery) for databricks.com. Implement automated accessibility testing and centralized consent management, unify frameworks into a shared design system, and operate within an AI-native, agent-assisted SDLC to drive platform features to production.

The Technology Program Quality Assurance Engineer enhances quality engineering in veterinary practice by leveraging technology for compliance, automation, and process improvement in quality management systems.

The Software Engineer, AI will develop intelligent systems for financial workflows, utilizing LLMs and other technologies to enhance bookkeeping and data processing for agriculture businesses.

Develop and optimize end-to-end data pipelines for autonomous driving, ensure data quality, and support model training through efficient data management processes.