Top Artificial Intelligence Jobs

Design and build AI-enabled automation tools, APIs, scripts, and workflows to streamline Verification & Validation processes. Implement generative AI use cases, integrate solutions with engineering systems and CI/CD pipelines, run pilots and transition to production, and collaborate with global teams to drive adoption and improve engineering efficiency.

Research and develop ML and statistical algorithms for networking, edge computing, cybersecurity, and autonomy. Build and evaluate simulation-driven solutions, lead subsystem software development, create automated tests, and contribute to proposals and technical plans while presenting results to customers and senior staff.

Lead design and delivery of scalable, production-grade agentic AI and automation systems integrated with enterprise collaboration tools (Slack, Outlook, Zoom, SharePoint, Copilot). Drive architecture-to-execution, CI/CD, infrastructure-as-code, monitoring, and cross-team collaboration to scale AI-driven workflows and improve associate productivity.

Design and produce a multi-module workshop series on Agentic AI for IT Support and Data Analytics: create lesson plans, scripts, demos, and 5–8 minute on-camera videos; build 30–45 minute hands-on workshops and performance-based assessments; translate real job tasks into progressive learning aligned to entry-level roles.

Design and validate autonomous experimental workflows; integrate robotics, instruments, sensors, and software; develop software and data infrastructure for instrument control, data acquisition, and experiment orchestration; apply AI/ML for experiment planning and analysis; troubleshoot platforms, collaborate across disciplines, and publish results.

Participate in a 24-month rotational AI program across portfolio companies to identify AI opportunities, design and deploy AI agents, models, and dashboards, translate analytics for stakeholders, and develop scalable AI solutions leading to post-program AI or analytics roles.

Lead end-to-end design for major enterprise/B2B features, defining problems, conducting research, executing high‑fidelity interaction designs, maintaining design quality and systems, mentoring designers, partnering with PM and engineering, and iterating post-launch with user feedback.

As the Senior Manager of Corporate Development Operations, you will lead M&A operations, utilizing AI for process optimization, data analysis, and reporting to the Board of Directors.

Develop, test, and maintain applications using Java, Python, or Node.js. Write clean, efficient code, debug and optimize, collaborate with cross-functional teams, use data structures/algorithms, work with SQL/NoSQL databases, participate in code reviews, and stay current on AI/ML concepts, agents, and automation tools.

Lead integration of AI into transportation products: prototype models, evaluate third-party tools, design fine-tuning/benchmarking strategies, oversee computer vision asset extraction, and apply AI to QA/QC with cross-functional teams to improve data integrity and product fit.

Lead US launch operations for Vocca: deploy and configure AI voice clients, own post-sale success and account management, document onboarding and playbooks, and achieve ~ $1M ARR in year one while building a scalable US ops function.

Lead the product strategy and roadmap for organic and AI-mediated discovery, translating SEO and AI platform shifts into product decisions. Build measurement, PLG loops, and trust signals for YMYL content, partner cross-functionally, and launch new distribution surfaces to drive qualified organic acquisition.

The Principal AI Engineer designs and implements AI systems to solve business challenges, focusing on advanced analytics and collaboration with teams, while ensuring compliance and managing risks.

Lead product operations for Canary's Voice AI: coordinate rollouts, drive adoption, run experiments and feedback loops, define KPIs, build dashboards, and partner with GTM to improve processes.

Design, evaluate, and deploy production AI agents that combine LLMs, retrieval, memory, and traditional ML. Build retrieval and memory pipelines, multi-agent systems, evaluation frameworks, and production guardrails. Run experiments and ablation studies, collaborate with infrastructure and enterprise customers, and measure business impact while ensuring reliability, safety, and observability.

Design, evaluate, and deploy production AI agents combining LLMs, retrieval, memory, and tool use. Build retrieval/memory pipelines, multi-agent systems, evaluation frameworks, and production engineering for reliable, safe enterprise AI deployments while partnering directly with customers.

Design, evaluate, and deploy production frontier AI agents that combine LLMs, retrieval, memory, tool use, and traditional ML. Build retrieval and memory systems, multi-agent coordination, evaluation frameworks, and production engineering (reliability, observability, safety). Partner with enterprise customers to translate problems into scalable AI architectures and run experiments to measure business impact.

The Senior Software Engineer will lead the development of AI solutions for the life insurance sector, overseeing full stack application design and delivery while guiding junior engineers.

Lead Solana Foundation's Bay Area strategy to drive AI × Solana adoption. Build relationships with AI/ML founders, VCs, and researchers; allocate capital and grants; launch flagship events; form strategic partnerships; and convert partnerships into shipped products. Must be Bay Area–based and accountable for regional outcomes.

Design, develop, and deploy machine learning and deep learning models; build and maintain production ML pipelines; preprocess and validate large datasets; implement APIs and integrate models into systems; monitor, optimize, and retrain models; collaborate with cross-functional teams to translate business needs into AI solutions.

Lead design, deployment, and operationalization of enterprise-scale ML and Generative AI systems. Build cloud-native MLOps platforms, oversee LLM and RAG deployments, ensure governance, scalability, security, and compliance, and manage teams of AI and MLOps engineers while partnering with cross-functional stakeholders.

Lead enterprise data strategy and design cloud-native lakehouse platforms. Build real-time and batch pipelines, architect generative AI (RAG, vector DBs, multi-agent), implement MLOps and feature stores, create BI solutions, establish governance, and lead/mentor technical teams while consulting with executive stakeholders.

Apply machine learning and AI models to real-world problems by designing, building, and deploying software systems. Implement end-to-end model workflows, ingest and transform large datasets, research and test advanced topics, verify software meets requirements, follow QA processes, document findings, and support engineering teams.

Lead and scale a team of FTEs and contractors to deliver Zip's AI products, drive customer adoption, own data and integration partner evaluations, ensure platform quality and reliability, manage delivery throughput from planning to deployment, develop automation/internal tools to reduce manual work, and partner with AI engineering, product, and customer success to resolve blockers and measure performance.

Serve as strategic HR business partner to the CTO and senior leaders for a 300-person global AI and software organization. Lead workforce planning, talent strategy, succession, leadership development, organizational design, large-scale change using Prosci/ADKAR, retention programs, and AI-enabled HR analytics. Drive executive advisory, build talent pipelines, and partner with finance, compensation, and TA to align people strategies with business outcomes.