Top Artificial Intelligence Jobs

Provide technical writing support for proposals, RFIs/RFPs, white papers, SOPs, user guides, and program deliverables. Translate technical/AI/ML content for non-technical audiences, standardize templates, maintain document libraries, create diagrams, ensure quality and compliance with DoD/intelligence standards and ISO 9001, and collaborate with SMEs and cross-functional teams.

Serve as the primary safety business partner for the Western region, leading safety performance, regulatory compliance, incident investigations, risk assessments, audits, and safety program implementation. Partner with operational leaders, analyze safety data, coach teams, support emergency response, and drive continuous improvement across FBO and aviation operations.

Lead the strategy, creation, and delivery of high-impact demos for Intapp’s Celeste agentic AI platform. Build hands-on prototypes using agents, integrations, playbooks, scripts, and sample data; identify compelling business use cases; present keynote demos and webinars; record and distribute demo assets to sales and solutions teams; and collaborate with product, marketing, sales, and leadership to refine the product narrative.

Build and own conversational voice AI products end-to-end: architect, implement, and deploy the platform. Design infrastructure, develop front-end and back-end systems, deliver reliable customer outcomes, and collaborate directly with the CTO to scale the product for enterprise customers.

Lead end-to-end Form 1042-S nonresident alien withholding and reporting, support 1099 reporting, drive reconciliations, data validation, automation, and controls; advise on cross-border tax events and partner with business, technology, and external stakeholders for system implementations and compliance.

The Data Scientist Level 4 develops strategies to extract insights from large datasets, utilizing advanced analytics and machine learning techniques. Responsibilities include statistical analysis, modeling, and effectively communicating findings to non-technical audiences.

Lead BIM strategy, implementation, and governance on complex building projects. Develop BEPs and CDEs (ACC/ProjectWise), manage model coordination/clash detection, integrate 4D/5D workflows, support digital handover and digital twin, automate workflows with Dynamo/Grasshopper, mentor teams, and maintain BIM standards and compliance with ISO 19650.

Supports generative AI application development by evaluating model quality, safety, accuracy, and performance; debugging and optimizing applications; preparing and validating data; and designing secure, scalable solutions with AWS Bedrock and Anthropic Claude. Reviews Python and ReactJS code, documents technical artifacts, tracks tasks, conducts research, and participates in team meetings.

Design and build a production multi-agent LLM framework and LLM-powered pipelines (text-to-SQL, NLU, structured reasoning). Implement RAG, prompt systems, evaluation and CI/CD for AI features, instrument and optimize model performance, and collaborate with product to deliver user-facing capabilities.

Label and outline plants in agricultural images using an online tool, tag crop and weed types per guidelines, maintain high accuracy across many images. Remote, flexible internship (3 months) with a monthly stipend and completion certificate. No coding or prior labeling experience required; video tutorials provided.

Lead architecture, implementation, maintenance, and optimization of RIS/PACS and CPACS systems. Provide level-three support, manage integrations (DICOM/HL7), mentor staff, lead large imaging projects, improve workflows via root-cause analysis and Lean, and maintain documentation, dashboards, and system performance.

Design, create, and implement AI and ML systems for Defense and Intelligence sectors, ensuring scalability and integration into various environments.

Lead design, training, deployment, and maintenance of AI/ML models for immigration-related datasets. Perform data architecture design, analytics, and DevSecOps CI/CD for classified AWS IL6 environments. Advise on security architecture, present findings to stakeholders, and support containerized, production-grade AI/ML solutions and model operations.

Lead design, build, and productionalize AI/ML models (LLMs, NLP, RAG, neural nets) for identity/immigration datasets in classified AWS IL6 environments, support architecture and DevSecOps CI/CD, present findings to stakeholders, and ensure security integration.

Lead design, training, deployment, and maintenance of AI/ML models (LLMs, NLP, RAG, neural nets) for a classified federal program. Build data architectures, containerized solutions, and DevSecOps CI/CD pipelines; perform analytics, optimize processes, support security architecture, and present results to stakeholders.

Design, train, and deploy ML models for Qur'ān recitation, tajwīd detection, and ASR. Build data pipelines for cleaning, segmentation, labeling, and evaluation. Integrate real-time predictions via APIs or lightweight on-device inference, optimize models for speed and mobile performance, and collaborate with backend developers to ship AI features in the app.

Advise technology CEOs at small and midsize providers on AI Orchestration, growth strategies, market dynamics, competitive positioning, product innovation, and leadership practices. Conduct market research and analysis, predict industry shifts, create actionable frameworks, and produce thought leadership content. Engage executives through meetings, conferences, and events; deliver presentations and collaborate with Gartner research teams.

Leads research and thought leadership on enterprise integration, APIs, AI gateways, LLM gateways, and Model Context Protocol. Advises executives and clients on integration strategies, team structures, vendor selection, governance, and emerging market trends. Produces high-value research, presentations, market analysis, and actionable recommendations; supports sales and conferences; collaborates across teams; reviews content; and mentors junior analysts. The role is an individual contributor requiring strong executive presence, communication, analytical, writing, and presentation skills, with travel up to 25%.

Lead technical direction and architecture for DAP Repository Flows, design and ship autonomous and scheduled agents that operate on customer repositories, improve DAP onboarding, collaborate across teams on platform interfaces, mentor engineers, and solve high-scale technical problems to raise engineering quality.

This is an open talent‑community posting inviting U.S.-based candidates across multiple disciplines (software, AI/ML, XR, UX/UI, DevOps, cybersecurity, data, instructional design, etc.) to submit a resume and brief introduction. HTX Labs will retain candidate information for future contract-to-hire opportunities. Must be authorized to work in the U.S.; no visa sponsorship available. Remote-first role supporting immersive learning for Department of Defense clients.

Design, build, and deploy production-grade ML and AI solutions for behavioral health. Architect end-to-end MLOps pipelines, optimize and monitor models in production, evaluate emerging AI trends, collaborate cross-functionally, and provide technical leadership and mentorship to engineering teams while ensuring responsible, scalable, and secure AI deployments.

Lead cloud migrations for voice contact center solutions, design AI/ML capabilities, improve automation and governance, and ensure production readiness while collaborating with cross-functional teams.

Lead design, development, and production deployment of AI/ML solutions and conversational chatbot platforms. Own end-to-end implementation, MLOps/CI-CD, containerized deployments, solution architecture, security and governance, mentor engineers, and collaborate with product, enterprise architecture, and vendors to deliver scalable, monitored AI systems.

Lead technical design and delivery of production AI/ML and GenAI solutions (RAG, LLMs, agents). Build, tune, deploy, and monitor models and APIs, own MLOps practices, operate cloud AI workloads, ensure software quality and responsible AI, and partner with cross-functional stakeholders while mentoring engineers.

Partner with CEO/CFO to deliver executive-grade data, own global forecasting engine, build causal inference and time-series models, drive generative AI strategy and production, and scale a data science and engineering team to inform capital allocation and long-range planning.