Top Artificial Intelligence Jobs

Build and deploy secure, production AI applications for tax and audit professionals, including RAG pipelines, custom agents, and agentic workflows. Develop scalable Python backend services, integrate with client and Thomson Reuters systems, and establish evaluation, observability, monitoring, and testing practices. Lead client delivery, translate ambiguous business needs into technical solutions, support deployments and incidents, and collaborate with AI engineers and senior technical leaders across multiple engagements.

Build and deploy reliable AI automations for tax and audit professionals. Responsibilities include understanding client workflows, designing controlled AI solutions, creating prompts and agents, developing prototypes with Python and low-code tools, validating accuracy through expert datasets and test harnesses, demonstrating solutions to clients, and collaborating with domain, editorial, product, and engineering teams. The role requires substantial tax or audit experience, professional judgment, and the ability to translate complex workflows into practical AI applications.

Build and maintain ERP and business-system integrations, automation, data transformations, and AI-enabled features. Translate requirements into tested, secure solutions; deploy, monitor, troubleshoot, document, and support implementations. Collaborate with engagement leaders, client IT teams, and business stakeholders while applying version control, testing, access controls, and human review for AI functionality. The role requires 3–5 years of relevant engineering experience, programming and SQL proficiency, and may involve up to 30% travel.

Leads Podium’s end-to-end demand generation function for a business vertical, owning revenue, pipeline, budget, ROI, channel strategy, and marketing efficiency. Manages and coaches a lean team across events, partnerships, webinars, media, lifecycle, and content marketing while collaborating with centralized digital, SEO, web, sales, product, finance, and revenue operations teams. The role requires hands-on execution, rigorous funnel analysis, experimentation, executive reporting, and AI-first marketing workflow development. This position is onsite five days per week in Lehi, Utah.

Drive AI adoption and measurable outcomes across strategic enterprise technology accounts. Build executive relationships, guide customers on Claude products, optimize usage, develop ROI cases, manage account success plans, lead change management and enablement programs, and identify expansion opportunities. Partner cross-functionally to communicate product roadmaps, influence product development, and help customers scale AI use cases across their organizations.

Design and implement AI-driven workflows, multi-agent systems, and enterprise automations using low-code/no-code platforms, LLMs, APIs, retrieval architectures, and business-system integrations. Partner with cross-functional teams to identify automation opportunities, translate operational needs into scalable solutions, and establish monitoring and governance. Integrate platforms such as Salesforce, SAP, Slack, Teams, SharePoint, and Workday while continuously improving AI orchestration capabilities.

Architect and build Traba’s AI agent platform, including orchestration, model strategy, retrieval, memory, tools, evaluation, observability, and integrations with WMS, TMS, ERP, and customer systems. Lead foundational technical decisions, spend time with customers to shape deployments, establish quality and reliability standards, hire and mentor engineers, and partner with company leadership on the platform roadmap.

Build and scale Traba’s AI-powered staffing marketplace by integrating existing AI agents and frontier models into product workflows. Develop frontend and backend systems for worker vetting, matching, fulfillment, payments, real-time matching, distributed services, and APIs. Own product surfaces end to end, collaborate with product and design, mentor engineers, and partner with the CTO on architecture and roadmap.

Build and lead Traba’s AI-powered staffing platform, integrating frontier models and agents into production workflows. Architect scalable backend systems for real-time matching, autonomous vetting, data processing, and platform infrastructure. Own technical architecture, performance, reliability, and scale while partnering with the CTO and contributing to roadmap decisions. The role requires strong full-stack experience, distributed systems expertise, and proficiency with TypeScript/Node.js or Python, PostgreSQL, and messaging systems.

Build production AI agent systems for industrial supply chain workflows, including agent harnesses, tool use, sub-agents, retrieval, orchestration, evaluation frameworks, APIs, and integrations with WMS, TMS, and ERP systems. Partner with customers, operators, product, and engineering to understand operational needs, deploy reliable agents, improve model performance, and create repeatable deployment patterns. The role requires strong software engineering, LLM production experience, and comfort working across backend services, data systems, and customer-facing solutions.

Design and implement AI solution architectures addressing finance and client business needs. Build prototypes and applications using AI, GenAI, LLM engineering, Python, and real-world data transformation. Apply finance expertise in FP&A, budgeting, forecasting, and reporting. Develop innovative solutions, assess feasibility and ROI, address AI risks, mentor team members, and work independently while aligning solutions with organizational strategies and ethical requirements.

Develop, deploy, and analyze AI/ML solutions for wired and wireless signaling data. Build software using neural-network libraries and Python, C, or C++, apply RF and digital signal processing knowledge, benchmark and optimize trained models, and solve complex problems collaboratively. The role may guide junior employees, support Agile modernization and automated testing, requires a STEM bachelor’s degree, eligibility for TS/SCI clearance with polygraph, and travel up to 25%.

Own enterprise customer outcomes, adoption, and value realization for industrial AI deployments. Lead complex implementation programs, technical workshops, and solution discussions while coordinating engineering, product, delivery, sales, and customer stakeholders. Translate AI insights into operational improvements, support account expansion, and develop long-term strategic partnerships with industrial organizations.

Leads operational readiness, integration, reliability, governance, and lifecycle management for AI and emerging technology services within enterprise collaboration and productivity platforms. Establishes production standards, runbooks, support models, monitoring, security controls, integration patterns, release processes, vendor coordination, and financial reporting. Coordinates architecture, engineering, security, compliance, operations, and application owners to transition approved capabilities from incubation or pilots into sustainable production services.

The Senior Customer AI Engineer will support enterprise customers' AI Marketing efforts, focusing on integrations, technical solutions, and optimizing customer outcomes while maintaining effective communication across teams.

Develop technical AI and data solutions for aerospace engineering applications. Responsibilities include designing architectures, building proof-of-concepts, coding and debugging applications, developing machine learning systems, presenting solutions to stakeholders, and shipping cloud-based products to production. The intern will gain experience with data engineering, cloud platforms, databases, web design, AI technologies, and numerical methods while collaborating across teams.

Develop and demonstrate AI and data solutions for aerospace engineering projects. Responsibilities include designing architectures, building proof-of-concepts and machine learning systems, writing code, creating demos, supporting cloud and data engineering initiatives, and delivering production-ready solutions. The intern will collaborate cross-functionally, participate in design thinking, gain mentorship, and work on real-world projects using technologies such as Python, cloud platforms, machine learning, LLMs, and computer vision.

Research Engineer improving AI security agents through agent reasoning, evaluation, benchmarking, model selection, security hardening, and reliability engineering. The role develops production-quality systems that detect vulnerabilities, resist prompt injection and data exfiltration, validate findings, and learn from customer engagements. Responsibilities span research and engineering, including experiments, graders, benchmarks, multi-step planning, model tuning, and security research for LLM-based applications.

Architect and implement production AI/ML systems with emphasis on generative AI and agentic systems. Conduct data analysis, design experiments, build evaluation frameworks, integrate models into products, ensure compliance, and guide enterprise AI standards and best practices.

Conduct advanced AI/ML research and develop novel methods, models, and mission-focused technologies. Build, train, validate, and integrate deep learning systems using modern frameworks and GPU hardware. Research areas include adversarial, trustworthy, safe, agentic, deep, and generative AI. Communicate findings through publications, technical reports, presentations, and study plans while collaborating with interdisciplinary teams and leading technical tasks.

Drive sales and adoption of Azure and AI among high-potential software startups. Build executive relationships, manage a strategic startup portfolio, coordinate Microsoft technical, business, and partner resources, qualify Azure AI pipeline, enable Marketplace and co-sell readiness, and execute deals that generate customer and Microsoft revenue.

Leads complex enterprise ERP and AI business application sales opportunities across the Americas. Builds executive and partner relationships, uncovers Dynamics 365 and Copilot opportunities, gathers requirements, develops solution demonstrations, and guides customers from envisioning through production deployment. Partners with account teams, engineers, customer success teams, and Microsoft partners to establish business sponsors, user cohorts, value cases, and sustained consumption. Success is measured through customer usage, realized value, and consumption revenue.

Partner with business functions to map workflows, identify AI automation opportunities, and create prioritized solution briefs for Forward Deployed Engineers. Develop ROI-based business cases, document requirements, support delivery and user acceptance testing, drive adoption, report value, and analyze post-deployment impact. Coordinate engagements, mentor junior analysts, and codify the AI business analyst operating model across the enterprise.

Develop and deploy full-stack software applications using C#/.NET, Tungsten Automation, SaaS, AI/ML, OCR, and generative AI. Build intelligent document-processing workflows, classification and extraction solutions, dashboards, integrations, and custom applications connected to enterprise repositories and systems of record. Perform code migration, testing, CI/CD deployment, production support, version control, change management, and security management across an agile software lifecycle.

Develop and deploy AI applications, backend GraphQL scripts, automated testing frameworks, and single- and multi-agent workflows. Collaborate with stakeholders, solution and UX architects to identify AI opportunities and deliver user-friendly experiences. Document development work, design evaluation processes, optimize code, and help maintain production-quality standards. The intern will apply AI frameworks, LLM concepts, prompt engineering, and modern web development technologies to real-world projects.