Top AI Engineer Jobs

Develop and integrate generative AI and LLM-based capabilities into mission-critical warfare systems. Use AI-augmented engineering tools across the software lifecycle, prototype agent frameworks, and mentor teams on secure AI development. Collaborate with cross-functional stakeholders to operationalize AI models, build NLP pipelines, and improve developer productivity.

Lead design and delivery of enterprise-scale data lineage and metadata platforms. Build cloud-native, event-driven backend services and streaming pipelines using Java/Python on GCP. Partner with architecture, governance, and product teams to improve metadata ingestion, lineage discovery, automation (including GenAI), observability, and operational reliability while mentoring engineers and championing CI/CD and secure practices.

The AI Product Engineer will design, build, and ship AI features for clean energy finance while collaborating with various stakeholders to improve transaction processes.

The Senior Full Stack Engineer will enhance customer onboarding and AI financial planning features by building robust systems and leading engineering best practices.

Seek a Senior Back End Engineer to develop AI-driven applications, mentor engineers, and solve complex engineering challenges while focusing on scalability and data integrations.

Build and maintain full‑stack AI applications using Python, React/Next.js and .NET. Develop Generative AI, LLM, agentic and RAG-based solutions, implement PEFT (LoRA/mLoRA), MLOps/LLMOps pipelines, deploy on Azure, ensure security/compliance, mentor junior developers, and support underwriting/claims/operations integrations.

Design and implement a virtual access layer to enable remote use of a physical AI lab, building scalable, secure infrastructure to process 100,000+ documents/day with LLMs, optimize GPU/LLM throughput, provide customizable interfaces, implement authentication/access controls, and lead projects from design to production.

Hands-on founding engineer building a production Shopify app, storefront widget, video upload flow, and AI extraction pipeline. Ship, harden, and operate full-stack systems, ensure reliability and conversion-focused UX, and scale tooling for self-serve merchant onboarding.

Build and operate an on-prem AI platform (Model-as-a-Service) including RAG pipelines, vector DBs, MCP tooling, agent repositories, CI/CD integration, and guardrails within MRM. Optimize large on-prem GPU infrastructure and translate business use cases into scalable platform services.

Design, test, and document prompts and prompt libraries to optimize AI language model outputs. Collaborate with product, data, and ML engineers to integrate prompt solutions, run A/B experiments, measure performance, and maintain versioned documentation. Support TIBCO-specific implementation and stay current on AI/NLP techniques.

Design, develop, and deploy machine learning and deep learning models; build end-to-end ML pipelines including preprocessing, training, evaluation, and deployment; perform feature engineering on large datasets; deploy and monitor models on cloud platforms; collaborate with cross-functional teams to integrate AI solutions and retrain models as needed.

Design, build, and deploy production-grade ML and AI systems end-to-end, combining classical ML, deep learning, and LLM/agentic integrations. Implement MLOps, monitoring, CI/CD, model serving, vector search/RAG pipelines, and scalable APIs; mentor engineers and drive engineering best practices.

The Senior AI/ML Engineer will design, develop, and deploy scalable ML systems focusing on LLM applications, collaborating with various stakeholders to enhance healthcare data insights.

As a Senior AI Developer Technology Engineer at NVIDIA, you'll design and optimize AI and HPC workloads, solve performance issues, and influence future hardware and software design.

The role involves researching and developing GPU-accelerated AI workloads, optimizing algorithms, and collaborating with technical experts to improve hardware performance.

Lead design, development, and production deployment of intelligent agent systems that plan and execute tasks autonomously. Build scalable architectures, integrate ML/LLM models, automate workflows, design evaluation metrics, and implement APIs. Collaborate with researchers, data scientists, and engineers, produce technical documentation, and ensure compliance, security, and reliability of agentic solutions across products.

Design, analyze, test, and deliver high-reliability mechanical hardware for a large satellite constellation. Own product lifecycle from concept through high-volume production and on-orbit operation, drive DFM, perform environmental testing, and collaborate on system-level requirements and optimization.

Design, train, evaluate, deploy, and monitor large-scale ML systems (LLMs and bandits) for Duolingo Monetization. Collaborate cross-functionally, drive product decisions, mentor engineers, and ensure scalable, high-quality solutions.

As a Staff Computer Vision AI/ML Engineer, you will lead a team to develop and deploy AI/ML algorithms in remote sensing, including analyzing datasets and training deep learning models.

Lead end-to-end mechanical hardware design for a large-scale satellite constellation, including deployable radiators, large solar arrays, fluid distribution, and high-volume producibility. Drive system requirements, rapid design iteration, testing, DFM, supply chain/product lifecycle, and on-orbit performance. Own delivery from concept through production and launch, ensuring reliability, manufacturability, and cost-effective high-volume production.

Lead integration strategy and execution for Zoox's agentic platform. Collaborate with teams on tool integration, debug failures, and ensure resource readiness for production. Define integration artifacts and contribute to release processes.

As a Founding AI/Data Engineer, you'll design and build AI-driven products, collaborate across teams, and ensure system reliability while enhancing user experiences.

Lead design and deployment of AI-driven predictive maintenance solutions for facilities. Analyze workflows, build/train/deploy ML models, integrate sensor/IoT data, ensure security/compliance in a classified on-site environment, validate models, run stakeholder working sessions, and provide technical documentation and training.

Design and implement full-stack applications for GenAI, build developer tooling, collaborate with product teams, and enhance AI agent delivery.

Design and implement full-stack applications and AI agents to enable rapid development and deployment of AI solutions in critical industries. Mentor engineers and take ownership of projects while applying secure SDLC practices and collaborating with cross-functional teams.