Top Artificial Intelligence Jobs

Lead credit underwriting, approval, and portfolio oversight across commercial, commercial real estate, and private banking. Monitor portfolio performance, conduct credit reviews, manage problem loans, oversee appraisals, advise senior leadership, and coach credit analysts. Ensure regulatory compliance, enforce credit policy, and support portfolio strategy and governance.

Lead design and implementation of AI-first testing frameworks and automation to validate LLM integrations and agentic Product Led Growth workflows. Perform white-box testing, identify and fix quality gaps, implement human-in-the-loop model evaluation, and collaborate cross-functionally to integrate quality across the agile delivery lifecycle.

The National Account Consultant executes retention and growth strategies for enterprise accounts, implements AI solutions, ensures customer satisfaction, and manages communications and projects.

The Client Success Consultant manages client relationships, ensuring effective implementation and adoption of AI solutions, while identifying growth opportunities and maximizing retention.

Coordinate rural health program operations and mobile clinic logistics, including inventory management, vehicle operation, stakeholder coordination, technical requirements gathering (AI, mobile IT, cybersecurity), data tracking and reporting, and supporting project management tasks to improve access to care for rural communities.

The AI Marketer/DevRel will enhance brand awareness through technical content, community engagement, and storytelling while fostering developer relations.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Lead design, development, and deployment of LLM-powered solutions and autonomous procurement agents on the GEP AI platform. Advise stakeholders, run workshops, configure platform ontologies and data pipelines, optimize models for procurement tasks, and oversee cross-functional implementation to drive automation and improved procurement decision-making.

Design, evaluate, and deploy LLM-powered features end-to-end: prompt engineering, semantic retrieval, embeddings, vector stores, evaluation frameworks, and production integration while collaborating with product and engineering and working directly with users.

Answer inbound customer calls and chats using AI tools to troubleshoot and resolve issues, de-escalate frustrated customers, follow documented processes, and flag patterns to improve systems.

Lead design and delivery of an enterprise Agentic AI platform: architect production-grade LLM services, agent workflows, retrieval and vector search pipelines, and observability. Build scalable Python (FastAPI) and TypeScript/Node services, deploy on Kubernetes/AWS/Azure with CI/CD, implement AI governance and evaluation frameworks, mentor engineers, collaborate cross-functionally, and support customer engagements and technical documentation.

Lead enterprise AI adoption by defining roadmap, governance, and enablement programs. Partner with IT, data, security, and business leaders to prioritize AI initiatives, evaluate vendors and architectures, scale high-value solutions, improve data and knowledge readiness, build an AI champion network, and report measurable business outcomes and adoption metrics to executives.

Design, implement, and train state-of-the-art 3D reconstruction and egocentric optical flow models from scratch. Scale multi-view architectures across multi-GPU clusters, innovate losses/architectures, prototype perception solutions, integrate neural rendering (NeRF, Gaussian Splatting), and produce motion-aware outputs for downstream robotics.

Design and productionize ML models and agentic systems for intraday financial alpha generation. Build data pipelines, experiment frameworks, and portfolio optimization methods. Collaborate with quants and engineers to move models from research to live trading environments.

Assist in designing, developing, testing, and deploying enterprise AI applications focused on Generative AI, RAG, and agentic workflows. Support LangChain/LangGraph implementations, RAG pipelines, backend APIs, database integrations (Cosmos DB, SQL Server), Azure deployment and monitoring, CI/CD with Azure DevOps, prompt engineering, documentation, and cross-functional troubleshooting.

The AI Engineer will design and deploy classification models for media, optimize data pipelines, lead R&D in voice and audio generation, and research image intelligence technologies.

The role involves designing and implementing automation systems, improving workflows, and developing tools for sales support using AI and automation platforms.

The Local SEO & AI Presence Specialist executes localized search strategies, manages digital presence, collaborates with Account Managers, and optimizes content for local SEO and AI platforms.

Build and operate production private AI platform capabilities (agentic/multi-agent systems, orchestration, auto fine-tuning, runtime/model optimization). Implement evaluation, monitoring, safety/rollback controls, developer-facing APIs, and tooling. Partner with data and infra teams to ensure reliable, performant AI inference in constrained edge environments.

Support DISA by researching and applying AI technologies (ML, NLP, CV), developing and evaluating models, and aiding proofs-of-concept. Lead technical planning, quality/configuration management, produce documentation and briefings, and coordinate stakeholders to support RMF/STIG cybersecurity initiatives and mission outcomes.

Design and build production LLM-powered systems and agentic workflows, contribute to a core learning library, implement human-in-the-loop feedback and evaluation frameworks, work with enterprise customers to prototype and ship features, and architect scalable AI orchestration and confidence systems.

Research, design, and train foundation models for robotics; align text-based reasoning with low-level control policies; evaluate zero-shot generalization; run experiments; integrate models into robotic systems and present findings externally.

Optimize and compress large language and vision models for on-device inference. Build distillation and hardware-specific compilation pipelines, benchmark performance across NPU/GPU architectures, and deploy models to edge environments.

Design and architect multi-agent orchestration frameworks, build tool-calling pipelines and reasoning loops, and optimize latency and token usage for real-time agentic workflows and autonomous operations.

Optimize and compress large language and vision models for on-device inference. Build model distillation and hardware-specific compilation pipelines, and benchmark performance across various NPU/GPU architectures to enable efficient edge deployment.