Top Artificial Intelligence Jobs

Build, deploy, and operate production voice AI agents integrated with telephony and contact-center platforms. Design autonomous call workflows, author and version agent instructions and prompts, manage context and interruptions, and create automated evaluation for probabilistic voice behavior. Monitor safety, latency, containment, hallucinations, transcription accuracy, and tool usage. Work directly with customers in forward-deployed environments, translate requirements into testable specifications, and collaborate with product, design, and engineering teams.

Lead product strategy, roadmap, and delivery for Microsoft’s AI-native agentic security solutions. Partner with engineering, security research, design, data science, and enterprise customers to create products supporting threat detection, investigation, response, remediation, and security posture improvement. Drive cross-organizational alignment, product adoption, measurable customer outcomes, market disruption, and executive communication for large-scale cloud security products.

Advise Deutsche Bank businesses on anti-financial-crime risks involving FinTech, digital assets, new payment types, and emerging technologies. Develop globally consistent AFC strategies, policies, transaction-monitoring and sanctions-screening controls, and KYC requirements. Assess regulatory developments, client and transaction risks, and new technology risks while supporting blockchain analytics capabilities and cross-bank initiatives. Partner with internal and external stakeholders and represent AFC on relevant projects.

This role involves developing and maintaining CI/CD pipelines, enhancing deployment processes, ensuring infrastructure reliability, and promoting best practices within the AIDR platform team.

Teaches undergraduate and graduate artificial intelligence courses in a blended learning environment. Responsibilities include developing syllabi and lesson plans, preparing course materials, facilitating online and face-to-face instruction, creating and grading assessments, providing timely feedback, and supporting responsible AI use in academic work. The instructor also participates in faculty training and ongoing professional development.

Provides technical leadership for enterprise systems development, including project planning, requirements analysis, software design, coding, testing, debugging, documentation, integrations, upgrades, and production turnover. Leads complex programming initiatives, coordinates project activities, communicates with customers, maintains automated business processes, and mentors technical staff. The role also supports process improvement, user training, troubleshooting, quality activities, and project management coverage.

Design and build foundational web services, service mesh infrastructure, developer tooling, CI/CD automation, and highly reliable distributed systems. Architect scalable APIs and data consistency patterns, optimize high-throughput systems, establish observability and reliability practices, and mentor engineers. The role supports millions of transactions across mobility products and requires collaboration across application, infrastructure, and advanced technology teams.

Leads first-line sales managers and enterprise account teams selling Splunk and Cisco solutions to U.S. Federal Civilian agencies. Owns multi-million-dollar revenue targets, territory strategy, pipeline development, forecasting, executive customer relationships, partner GTM campaigns, and cross-functional solution delivery. The role covers cybersecurity, observability, data platform, and AI offerings across major federal departments and requires up to 30% travel.

Develop and support scalable full-stack software using Java, Spring Boot, React or Angular, Python, APIs, microservices, and cloud technologies. Lead architecture, AI-enabled capabilities, testing, troubleshooting, observability, automation, and performance improvements. Mentor engineers, conduct code reviews, influence technical direction, and independently deliver complex solutions across the software lifecycle.

Develop and support complex full-stack software solutions using Java, Spring Boot, React or Angular, and Python. Design scalable APIs, microservices, distributed systems, and cloud-based architectures while integrating AI and machine learning capabilities. Lead technical implementations, testing, troubleshooting, performance improvements, and operational readiness. Mentor engineers, conduct code reviews, influence architecture and engineering standards, and independently deliver complex features with minimal oversight.

Build and own full-stack AI systems for hospitality, including response generation, retrieval, tool orchestration, evaluation, observability, no-code controls, voice capabilities, infrastructure, data pipelines, and integrations. The role focuses on making AI agents reliable in real-world conversations with messy data and failing third-party APIs while optimizing performance and cost.

Leads complex, cross-functional engineering programs from development through product implementation. Manages schedules, deliverables, budgets, resources, project teams, risks, escalations, and stakeholder communications. Partners with engineering, manufacturing, development, and management teams to resolve issues, improve processes, and deliver products or services on schedule and within budget.

Serves as the strategic technical partner for global and regional alliances, leading pre-sales discovery, demonstrations, proofs of concept, solution architecture, and technical escalations. Advises partners on AI-enabled offerings, practice growth, go-to-market strategy, commercialization, and measurable business outcomes. Builds executive relationships, coordinates specialist teams, and translates ServiceNow platform capabilities into scalable partner solutions. The role requires enterprise technology advisory experience, partner engagement, AI and workflow knowledge, industry expertise, and up to 50% travel.

Supports Service Operations strategic initiatives through process improvement, staffing and capacity modeling, call and quality data analysis, risk insights, documentation, project tracking, AI use cases, and resource allocation. The intern collaborates with business leaders, subject matter experts, and IT professionals while contributing to service excellence and organizational planning.

Leads architecture and development of frontend manufacturing applications while establishing organization-wide standards for AI-assisted software engineering. Responsibilities include coding across .NET, C++, Angular, Perl, and Python; modernizing legacy systems; resolving production issues; evaluating AI tooling; governing AI-generated code quality and security; measuring productivity outcomes; mentoring senior engineers; and influencing technical direction across multiple teams.

Build and operate production-grade full-stack applications with AI as a core capability. Develop custom AI agents, MCP integrations, RAG systems, and AI-enabled engineering workflows. Own features end to end, including architecture, implementation, testing, deployment, observability, security, reliability, and lifecycle support. Collaborate with business and engineering teams while applying cloud-native practices, scalable system design, and rigorous evaluation of AI-generated outputs.

Architects and develops systems software for emerging memory and storage technologies, with emphasis on AI inference stacks and heterogeneous computing. Responsibilities include Linux application and library development, emulator creation, system-level debugging, accelerator programming, performance evaluation, technical leadership, cross-functional collaboration, mentoring, and presenting technical findings. The role requires expertise across AI frameworks, inference engines, operating systems, kernels, hardware interfaces, memory hierarchies, and distributed serving systems.

Research and evaluate memory architectures for generative AI, GPUs, TPUs, and other accelerator platforms. Develop system-level models measuring performance, power, scalability, and efficiency across memory and compute architectures. Investigate HBM, DRAM, cache, storage, and interconnect optimizations, including compute-near-memory concepts. Collaborate with cross-functional teams to translate research findings into architecture recommendations, product strategies, and long-term technology roadmaps.

Leads the design and operation of an integrated renewals and commercial operations function covering pricing, deal desk, contract negotiation, discount governance, and RFP resources. Redesigns processes using AI and automation, defines CPQ and contract lifecycle requirements, improves ARR and productivity, establishes commercial policies, monitors KPIs, and builds a high-performing team while partnering with Sales, Legal, and Finance.

Conduct applied AI and machine learning research focused on multimodal data, foundation models, agents, evaluation, and data enrichment. Monitor research trends, prototype emerging techniques, design experiments, validate opportunities, and translate findings into briefs and recommendations. Partner with product and engineering teams to guide data strategy, training corpus generation, and longer-term opportunity prioritization.

Lead federal civilian account strategy and sales for AI solutions, managing the full sales cycle from pipeline generation through deployment. Own revenue targets, forecasting, account metrics, deal strategy, and executive relationships while partnering with engineering, solutions, product, marketing, and business operations teams. The role also monitors federal market developments, supports customer events, and helps build the federal practice.

Leads complex technical programs for AI and robotics customers, translating research objectives into engineering requirements, project plans, milestones, and delivery processes. Coordinates research, engineering, hardware, data operations, and quality teams while managing scope, risks, resources, dependencies, and stakeholder communication. Oversees physical AI data-collection initiatives from solution design through execution, quality control, and final delivery, with emphasis on reliability, data quality, customer satisfaction, and scalable operating processes.

Lead Orbital’s US commercial growth, owning go-to-market execution, revenue targets, pipeline development, new business acquisition, account expansion, partnerships, and commercial negotiations. Champion the AI platform internally and externally through enablement, events, thought leadership, and executive relationships. Monitor market and competitive trends, support customer success, and build a high-performing commercial team.

Leads globally distributed software engineering teams delivering strategic healthcare, payment integrity, AI, and enterprise platform initiatives. Defines roadmaps, manages execution governance, operationalizes AI/ML and Generative AI capabilities, promotes responsible AI, and drives cloud architecture, DevOps, CI/CD, SRE, release management, and production operations. Partners with product, business, architecture, and executive stakeholders while monitoring delivery metrics and developing engineering talent.

Conduct applied AI and machine learning research spanning multimodal intelligence, recommendation, ranking, prediction, foundation models, agents, and decision-making. Define research problems, evaluate and develop models using proprietary data, run rigorous experiments, create training signals and evaluations, and transition successful approaches into production systems. Collaborate with engineering and product teams while shaping the company’s research agenda and technical standards.