Top Artificial Intelligence Jobs

Lead architecture and implementation of agentic AI systems powering Zuma's platform. Rebuild onboarding and integration frameworks, implement analytics and observability for LLM performance, translate product needs into technical solutions, mentor engineers, establish engineering standards, and work directly with customers to enable scalable, production-grade AI experiences.

Lead end-to-end development and production deployment of agentic AI systems and full-stack products. Architect integrations with property management systems, improve reliability and observability, define engineering standards, and partner with product and operations to ship scalable AI agents across voice, text, and email.

Produce AI-generated product imagery and presentation-ready visualizations; craft and refine AI-written content for proposals, RFPs, and marketing; build prompt frameworks and scalable workflows; collaborate with Sales, Design, Marketing, and RFP teams to prioritize and deliver on content requests while ensuring brand alignment.

Own full sales cycle for AI-driven energy management solutions across energy-intensive industries. Lead consultative technical and executive conversations, develop tailored proposals with engineering teams, build long-term stakeholder relationships, and maintain pipeline discipline to drive revenue and decarbonization impact.

The Principal Technical Program Manager will lead AI initiatives, oversee program execution, ensure cross-functional cooperation, and track AI project impact metrics.

Evaluate and strengthen AI model behavior on cybersecurity topics by writing expert prompts, annotating and grading model responses for accuracy and safety, and applying structured guidelines to classify sensitive content. Work part-time on AI safety tasks with emphasis on secure, responsible handling of dual-use information.

Lead end-to-end ML implementations for clients, design and maintain production-grade MLOps pipelines, deploy and optimize Generative AI/LLM and NLP solutions, manage infrastructure (Docker, orchestration, distributed compute), and communicate technical results to stakeholders.

The AI Engineer will design and implement scalable AI systems, collaborate with stakeholders, and influence AI strategy to integrate AI solutions into business operations while ensuring compliance with regulations.

Build and ship full‑stack, LLM-powered product features (tutoring agents, copilots, dashboards, retrieval and evals). Own smaller systems end‑to‑end, use AI coding tools daily, write evals and regression tests, and iterate rapidly with founders and senior engineers.

The AI-Enhanced Virtual Assistant will support AI integration, administrative tasks, communication management, project coordination, and client interaction to enhance operational efficiency.

As a Machine Learning Engineer, you will build agentic systems for autonomous web navigation and complex task completion, integrating LLMs and reinforcing learning.

The Senior Data & AI Consultant leads digital initiatives, designs enterprise data solutions, and mentors teams using the Microsoft data stack for analytics and AI enablement.

Design, train, test, deploy, and maintain AI/ML models (LLMs, RAG, agentic workflows). Build production-grade software and APIs, implement MLOps/DevSecOps, design event-driven integrations, and collaborate with engineers and product owners to deliver mission-critical solutions for Air Force operations.

The AI Enablement Engineer will integrate AI tools into engineering workflows, enhance productivity, and ensure compliance with data security standards while supporting engineers' adoption of AI solutions.

Design, train, test, deploy, and maintain AI models (LLMs, RAG, agentic workflows). Build production-grade APIs and data services, implement MLOps/DevSecOps, and integrate event-driven workflows to support Air Force mission solutions while collaborating with cross-functional teams.

The AI Application Engineer will design and develop applications using Large Language Models, implementing workflows, ensuring code quality, collaborating with teams, and deploying solutions on cloud platforms.

Design and evaluate transformer-based models for structured and time-series credit data. Analyze internal representations, run ablations and hyperparameter sweeps, build research prototypes in PyTorch/TensorFlow, and collaborate with ML engineering to productionize interpretable, discriminative, and generative modeling advances.

Drive user growth and go-to-market execution for a new AI voice agent product through various acquisition channels and strategies while collaborating with cross-functional teams.

Lead end-to-end AI deployments, working closely with enterprise teams to drive adoption, improve workflows, and deliver impactful AI solutions.

The Senior Consultant in AI will design, build, and deliver AI/ML solutions on Azure, engage with clients, and develop project components independently.

Lead architecture and delivery of enterprise AI agent solutions on the Moveworks/ServiceNow platform, integrating with enterprise systems. Build and tune AI workflows, partner with product and vendors, and provide L2/L3 IT operations support (servers, networks, virtualization, cloud). Act as help desk escalation, troubleshoot complex issues, and continuously improve IT processes.

Partner with university teams to identify practical AI use cases, lead discovery and adoption, evaluate tools, develop training and workshops, provide hands-on mentoring and support, and build documentation, toolkits, metrics, and feedback loops to sustain AI service adoption across campus.

The AI Account Executive drives sales growth for Expedient's AI CTRL services by acquiring new customers and collaborating with partners. Responsibilities include lead generation, managing the sales cycle, understanding product value, and maintaining records in Salesforce.

The AI Engineer will develop scalable AI systems, automate workflows, and collaborate with business teams to enhance operational efficiency across OpenSesame.

Lead the development of machine learning methods for AI-native metal manufacturing systems, focusing on integrating physical data with physics-based simulation.