Top AI Engineer Jobs

The Staff AI/ML Engineer will lead the development of AI systems for regulatory compliance, focusing on ML architecture, implementation, and oversight of model reliability.

Senior individual-contributor building production agentic AI and RAG systems end-to-end: document ingestion/OCR, chunking, embeddings/vector indexes, retrieval orchestration, prompt engineering, evaluation harnesses, FastAPI services, database schemas, governance controls, and mentoring mid-level engineers.

Lead architecture and delivery of production-grade agentic AI and RAG systems. Own multi-agent orchestration, embedding/vectorization pipelines, retrieval, evaluation frameworks, and team leadership for engineers building document-intelligence and AI-assisted developer tooling. Responsible for production delivery, observability, CI/CD, and cross-team integration in an enterprise finance environment.

Embed with strategic semiconductor customers to deploy LLM- and agent-based AI into end-to-end EDA flows (RTL through signoff). Architect agentic workflows, integrate Cadence AI products, define KPIs for productivity and ROI, guide secure LLM access and infrastructure, run design reviews, and produce reusable playbooks to scale deployments across sites.

Design and implement highly available, fault-tolerant full-stack web applications and services for Starlink. Build responsive TypeScript/React front-ends, .NET microservices running in Kubernetes, monitoring/alerting, and collaborate across teams to improve architecture, observability, and user experience.

Design, develop, and deploy production-grade AI/ML models and scalable architectures. Lead model training, validation, deployment, monitoring, and cross-functional integration. Conduct research, document methods, and share knowledge to drive business impact and operational reliability.

The Senior Vision AI Engineer will develop and deploy computer vision and machine learning models, create optimized vision pipelines, and mentor junior engineers, focusing on industrial applications.

The AI Analytic Software Engineer-Senior will lead AI and analytics solutions development, ensuring compliance and governance within a federal environment, integrating APIs and building front-end experiences.

As a Senior AI Systems Performance Engineer, optimize and scale foundation models, enhance performance across various system layers, and deliver high-performance AI applications.

Run technical discovery with customers, design and build end-to-end data integrations into Spiral, implement ingestion code and infra-as-code, operate orchestration and monitoring, reconcile and backfill data, and own post-go-live schema and feed changes while collaborating with Sales and CX teams.

Design and implement scalable cloud services, build APIs, integrate AI agents into development, and improve system reliability while collaborating with cross-functional teams.

The Senior Infrastructure Software Engineer will architect and scale multi-cloud infrastructure, focusing on compliance, observability, and developer efficiency for enterprise AI deployments.

Lead company-wide AI-native transformation by designing and implementing a unified LLM/AI platform. Embed with autonomous driving teams to operationalize LLMs, optimize distributed training and inference, improve GPU utilization, and build resilient MLOps/LLMOps pipelines while setting technical roadmap and driving cross-functional adoption.

Lead platform automation and AI-driven tooling for Ticketmaster's Global Host Platform. Write maintainable code, build IaC and containerized deployments, design agentic LLM workflows, drive adoption of AI developer tools, reduce tech debt, set SRE standards, mentor engineers, and run on-site trainings and periodic travel to improve reliability and automation at global scale.

As a Site Reliability Engineer for AI platform, you will ensure system reliability, develop automation, manage infrastructure, and evaluate new technologies.

Lead design and implementation of Copilot AI experiences and platform services across Windows, Mac, and mobile. Build secure, performant, distributed systems integrating models and agentic workflows, collaborate with cross-functional teams, ship well-tested maintainable code, and drive iterative product delivery.

Design, build, test, deploy, and maintain cloud-based applications, microservices, and infrastructure. Ensure application performance and quality, fix bugs, write automated tests, and collaborate on new features. Use AI-assisted development tools daily and implement IaC and modern architecture patterns to deliver secure, maintainable code.

Embed with client finance teams to design, build, and deploy production-grade agentic AI workflows. Develop multi-agent orchestration, integrate LLMs with enterprise systems (ERP/CRM/EPM), package agents as containerized microservices, implement CI/CD and monitoring, and ensure SOX/audit readiness. Mentor junior engineers, contribute reusable accelerators, and lead client-facing delivery under compressed timelines.

Senior AI Software Engineer responsible for designing, developing, and deploying generative AI, LLM-powered, and agentic AI systems. Lead system architecture, implement secure cloud-native deployments and CI/CD, collaborate cross-functionally, monitor and optimize production AI, mentor engineers, and enforce technical rigor and documentation for mission-focused federal solutions.

Design, develop, test, and support scalable AI/ML-powered enterprise applications and microservices. Implement LLMs, Generative AI, and RAG solutions; build RESTful APIs, automated tests, CI/CD pipelines; troubleshoot production issues and collaborate in Agile teams.

Build and maintain evaluation, monitoring, and CI systems to ensure AI quality, reliability, and compliance. Track metrics, detect drift, improve prompting, model selection, and pipelines, productionize robust AI workflows, support audits (SOC 2), and act as a quality gate for AI-related releases.

Design, develop, and deploy document AI and multimodal pipelines (OCR, LLM reasoning, extraction validation). Lead pre-sales technical engagements, build POCs/demos, support sales with technical value propositions, deploy solutions across cloud and enterprise VPCs, and collaborate with product and partners to drive customer adoption and roadmap feedback.

Provide SETA support to government teams building and evaluating AI-enabled applications. Advise on AI design, prototypes, integration, and technical risk. Assess LLMs, RAG, agentic workflows, orchestration frameworks, and evaluation harnesses. Review architectures, recommend engineering tradeoffs, develop prototypes and guidance, and support test and evaluation. Collaborate with platform engineers, product leads, and mission users to ensure operational relevance and maintain current knowledge of emerging AI tools and practices.

Provide technical advisory and hands-on AI engineering support for design, evaluation, and advancement of AI-enabled applications. Assess LLMs, RAG, agentic workflows, orchestration frameworks, and architectures; develop prototypes, guidance, and technical recommendations; support test and evaluation activities and brief government stakeholders while ensuring operational relevance.

Lead design and implementation of customer-facing AI features and foundational AI infrastructure (orchestration, retrieval, evals, context management). Identify high-leverage opportunities, create reusable AI primitives, set technical direction, and drive adoption through cross-functional collaboration and product-focused execution.