Top Artificial Intelligence Jobs

Implements AI-powered solutions for legal operations, including contract review, redlining, diligence, self-service workflows, chatbots, and legal system integrations. Develops program plans, dashboards, governance processes, and productivity improvements while coordinating with Engineering and Product teams. Translates legal business needs into scalable technical solutions and manages risks across multiple initiatives.

Designs, implements, governs, and improves AI-enabled marketing workflows and integrated systems. Responsibilities include process analysis, automation architecture, API integrations, data validation, content and reputation-management workflows, campaign tracking, testing, monitoring, access controls, documentation, user training, and incident recovery. Advises stakeholders on automation priorities, evaluates emerging AI capabilities, and maintains an automation roadmap while ensuring privacy, security, communication, and consumer-review compliance.

Leads the design, development, evaluation, and production operation of healthcare AI products, including agentic workflows, RAG systems, model optimization, guardrails, and human-review controls. Partners with product, clinical, engineering, data, platform, and security teams to build safe, reliable, observable, and compliant AI systems. Provides technical leadership through architecture, code reviews, incident response, mentoring, and delivery of HITRUST-aligned solutions for regulated healthcare environments.

Design and rapidly build Agentforce-powered AI solutions, prototypes, and demonstrations for client engagements. Lead technical client interactions, translate requirements into agent architectures, troubleshoot flows, Apex, integrations, and execution issues, and connect technical outcomes to business metrics. Collaborate with pursuit architects, manage iterative feedback, identify delivery constraints, conduct live demonstrations, and create reusable solution accelerators. The role requires strong enterprise architecture, rapid prototyping, stakeholder communication, and hands-on experience with Salesforce and agentic AI platforms.

Build and demonstrate rapid Agentforce-powered prototypes, agentic architectures, and proof-of-value solutions for clients. Lead technical design, tuning, troubleshooting, live demonstrations, and recurring stakeholder engagements. Translate technical decisions into business outcomes, resolve integration and execution issues under tight timelines, and create reusable accelerators. The role requires client-facing solution engineering, Salesforce and Agentforce expertise, rapid prototyping, enterprise architecture knowledge, and executive communication skills.

Build challenging AI coding tasks from familiar repositories, including task briefs, correct solutions, grading checks, stress tests, and model evaluations. Revise tasks through quality review and produce work suitable for training and assessing AI coding models. Requires at least 10 hours weekly and strong software engineering, testing, repository, and AI coding tool experience.

Build and deploy production AI solutions that improve business workflows, including AI agents, copilots, RAG applications, automations, and decision-support tools. Partner with cross-functional teams to identify opportunities, translate requirements, integrate enterprise systems and data sources, establish testing and governance, support adoption, and continuously improve solutions. The role requires hands-on software engineering, modern AI development, cloud integration, evaluation, deployment, and stakeholder communication.

Develop and support enterprise Generative AI applications, LLM integrations, RAG solutions, AI agents, chatbots, and intelligent automation using Python and cloud AI services. Build APIs, data pipelines, and vector database integrations; support model evaluation, deployment, monitoring, MLOps, and LLMOps. Collaborate with technical and business teams, troubleshoot systems, document solutions, and participate in Agile development.

Design and lead enterprise AI systems using generative AI, RAG, knowledge graphs, and autonomous agents. Define technical strategy, evaluate emerging AI technologies, and guide architecture and roadmaps. Mentor engineers, champion MLOps and LLMOps governance, and ensure security, testing, monitoring, and observability. Collaborate with research, engineering, design, and product teams to deliver scalable customer-facing solutions while optimizing latency, cost, and user experience.

Supports clients with advanced data analysis, AI strategy, recommendations, and presentations. Builds AI-assisted prototypes, automations, and internal tools using Claude Code, Gemini CLI, or Codex. Applies GenAI concepts such as prompting, RAG, agents, and context engineering, while coordinating project efforts and contributing to proposals and thought leadership.

Leads Everlaw’s user research strategy, roadmap, and team while personally conducting strategic studies on complex legal and AI workflows. Partners with Product, Engineering, Marketing, and Data Science to translate mixed-method research into compelling narratives, product strategy, and decisions. Develops researchers, establishes rigorous research standards, and scales the function through self-service frameworks, AI-enabled tools, and operational systems.

Leads people management, workforce planning, hiring, capability development, and delivery sustainability for an AI Tools engineering team. Oversees teams building governed AI agents, semantic systems, knowledge graphs, retrieval and data pipelines, evaluation, governance, and platform services. Partners with technical, architecture, product, analysis, and project leaders to translate AI strategy into actionable team context while preserving technical ownership. Develops leaders, improves management systems, supports responsible AI practices, and reduces operational and knowledge-continuity risks.

Lead and support end-to-end Rillet ERP implementations for CFOs and Controllers, configuring accounting workflows, developing delivery best practices, supporting scoping and sales handoffs, and ensuring timely, high-quality client outcomes. The role requires strong accounting knowledge, US GAAP expertise, ERP familiarity, client communication skills, and the ability to translate finance requirements into scalable system configurations and automations.

Lead and support end-to-end Rillet ERP implementations for CFOs and Controllers, configuring accounting workflows, translating finance requirements into automated systems, and contributing to consulting playbooks. The role also involves client scoping, sales handoffs, stakeholder communication, and delivering projects on time. Candidates need hands-on accounting or finance experience, strong US GAAP and close-process knowledge, ERP familiarity, and the ability to work autonomously in a hybrid consulting environment.

Evaluates AI coding-agent interactions for technical quality, engineering judgment, reasoning, explanations, and user trust. Provides detailed written and recorded feedback, distinguishes response quality levels, and helps define standards for tools such as Codex, Claude Code, and Cursor. This remote contract requires strong TypeScript, JavaScript, or Python experience, familiarity with AI-assisted development workflows, and senior-level engineering judgment.

Evaluate AI coding agents such as Codex, Claude Code, and Cursor for engineering judgment, response quality, reasoning, explanations, and usefulness. Provide clear written and recorded feedback, distinguish quality levels, and help define standards for excellent AI-assisted development interactions. This contract role requires senior-level software engineering experience, strong Python or TypeScript/JavaScript skills, familiarity with modern AI development workflows, and excellent English communication.

Evaluate AI coding agents such as Codex, Claude Code, and Cursor for engineering quality, reasoning, explanations, usefulness, and judgment. Provide clear written and video feedback, distinguish response quality levels, and help define standards for excellent AI-assisted development interactions. This contract role requires senior-level engineering experience, strong communication, familiarity with AI development workflows, and the ability to assess code without executing or reviewing every line.

Evaluate AI coding-agent interactions for correctness, usefulness, reasoning quality, engineering judgment, and user trust. Provide clear written feedback, distinguish response quality levels, help define evaluation standards, and record short video explanations. The role requires senior-level software engineering experience, strong JavaScript/TypeScript or Python skills, familiarity with AI-assisted development tools, and excellent written and spoken English.

Evaluate AI coding agents such as Codex, Claude Code, and Cursor for reasoning quality, engineering judgment, explanations, and usefulness. Provide detailed written and recorded feedback, distinguish response quality levels, and help define standards for effective AI-assisted development workflows. This remote contract requires 10–20 hours weekly, with ongoing projects lasting two weeks to several months.

Leads sales strategy and operations for mergers and acquisitions, including due diligence, GTM integration planning, sales operating model design, launch readiness, and post-acquisition execution. Coordinates cross-functional teams across Sales, Corporate Development, Finance, Product, Legal, and Operations. Develops integration playbooks, tracks milestones and risks, establishes reporting mechanisms, and supports pricing, quotas, compensation, systems, forecasting, and quote-to-cash workstreams.

Leads enterprise AI, data, automation, governance, and analytics strategy. Builds and manages data science, database, AI/ML, and automation teams; oversees platforms, projects, budgets, vendors, and business process improvements. Establishes data governance, quality, security, compliance, and AI ethics standards while delivering BI and predictive insights. Partners with executives and stakeholders to prioritize investments, manage risks, and align technology initiatives with strategic objectives.

Leads the discovery, development, evaluation, deployment, and adoption of AI workflows for clinical operations and clinical development. Builds Python prototypes and production code, designs agentic systems with human review and evidence provenance, establishes data governance and compliance controls, measures technical and operational outcomes, and partners with clinical, engineering, quality, regulatory, privacy, and executive stakeholders. Mentors technical teams and drives reusable enterprise AI capabilities.

Design, develop, test, document, troubleshoot, and debug complex software for semiconductor equipment components and devices. Define software specifications and test plans for simulators, test benches, and laboratory environments. Analyze requirements, implement bug fixes, communicate with internal and external customers, and contribute to machine learning and AI-driven software solutions.

Manage AI@HHMI research projects from approval through closure, including proposals, milestones, budgets, staffing, recruiting, events, partnerships, records, and leadership reporting. Coordinate with scientists, engineers, finance, legal, technology transfer, People & Culture, and communications teams. Support hiring, onboarding, offboarding, contracts, outreach, and project documentation while using AI tools to improve workflows.

Build and administer Ziegler’s AI-enabled marketing operations ecosystem. Design AI agents, Copilot workflows, marketing automations, integrations, knowledge repositories, and self-service tools. Support campaign execution, segmentation, lead routing, reporting, and customer journeys while improving efficiency and data quality. Establish AI governance, monitor and troubleshoot workflows, maintain taxonomies, evaluate emerging platforms, train users, and collaborate with Marketing, IT, Data, and business teams on secure, scalable implementations.