Top Artificial Intelligence Jobs

Leads Anthropic’s Forward Deployed Engineering organization, hiring and developing engineers, overseeing enterprise customer engagements, reviewing architectures and code, and establishing repeatable deployment playbooks. The role partners with Sales, Product, and Engineering to translate customer insights into product improvements. It is a player-coach position requiring technical discovery, prototyping, debugging, operational planning, and executive-level customer communication. Travel to customer sites is required 25–50% of the time.

Lead and grow a high-performing engineering team while remaining hands-on with architecture, system design, code review, and technical decisions. Own roadmap planning and delivery, build scalable and reliable infrastructure, improve observability and performance, and partner with product, design, and leadership to solve ambiguous problems. The role also involves hiring, mentoring, developing engineering culture, and ensuring systems deliver measurable customer impact.

Design, build, deploy, and operate secure, scalable AI-enabled products and internal tools. Evaluate models and services, develop prompts and context strategies, establish evaluations, monitoring, safeguards, and reusable architectures, and guide responsible AI adoption. Partner with product and engineering teams to prioritize opportunities, balance value and risk, mentor colleagues, and improve AI systems using production data and stakeholder feedback.

Develop and support AI-powered applications, automation solutions, and agent-based systems for business operations. Responsibilities include software development, integrations, Azure AI configuration, RAG and prompt engineering, testing, architecture participation, monitoring, troubleshooting, documentation, security collaboration, code reviews, and user enablement. The role works cross-functionally with engineers, stakeholders, legal teams, data professionals, and technology partners to deliver scalable and reliable AI solutions.

Design, build, evaluate, and deploy scalable AI models for insurance business problems. Analyze large datasets, validate models, monitor performance, and collaborate with data scientists and engineers to align solutions with business objectives and communicate results to non-technical stakeholders.

Leads enterprise-wide AI transformation across Finance, Supply Chain, Sales, and Marketing. The role redesigns core processes such as Quote-to-Cash and Procure-to-Pay using AI agents, LLMs, intelligent automation, and cloud AI platforms. Responsibilities include building transformation roadmaps and ROI cases, partnering with executives, leading cross-functional delivery teams, establishing AI transformation methodology, driving adoption and change management, and ensuring governance, schedule, performance, and business outcomes.

Designs and scales AI-powered simulations, role-play scenarios, and technical learning experiences. Owns prompt engineering, AI tool evaluation, simulation roadmaps, quality governance, accessibility, and performance measurement. Partners with Learning and Development, Product, Engineering, facilitators, and subject matter experts to translate learning needs into technical requirements and scalable training solutions. Uses analytics to improve skill transfer, time-to-competency, and business outcomes.

Designs and maintains the College’s enterprise data and AI platform. Develops integrations, governed data pipelines, warehouses, APIs, MCP services, dashboards, analytical applications, and AI-supported workflows. Establishes testing, monitoring, security, access controls, data governance, and evaluation standards. Partners with institutional offices to translate business needs into secure technical solutions while investigating unfamiliar systems, APIs, schemas, and workflows.

Build production AI systems combining voice interfaces, browser agents, computer vision, and large language models. Responsibilities include developing speech-to-text and text-to-speech systems, browser automation, prompt and LLM workflows, multimodal pipelines, evaluation frameworks, real-time infrastructure, observability, and production performance improvements.

The Principal Software Development Engineer leads the architecture and delivery of AI-driven healthcare applications, overseeing full stack development and collaborating with stakeholders to align technical solutions with business needs.

Supports research, evaluation, testing, and implementation of AI and digital tools across manufacturing operations. Identifies automation opportunities, analyzes business data, develops dashboards and process improvements, documents findings, creates training materials, and presents recommendations to leadership. The intern collaborates across departments while supporting responsible AI practices involving privacy, accuracy, confidentiality, and human review.

Lead financial due diligence engagements for private equity firms, corporate acquirers, and lenders across buy-side and sell-side M&A transactions. Oversee Quality of Earnings, Net Working Capital, Net Debt, cash flow, and financial analyses; manage client relationships, teams, quality control, engagement economics, and executive-level reporting. Advise on deal strategy and transaction mechanics, review SPA and APA documentation, mentor staff, support business development, and advance technology-enabled diligence approaches.

Provides outpatient body imaging radiology services through a combination of remote and onsite daytime shifts. Reads primarily within the body imaging subspecialty, collaborates with referring providers, and supports immediate care coverage without ER or inpatient responsibilities. The role includes no procedures or fluoroscopy, flexible scheduling, minimal weekend and evening work, and opportunities for leadership, partnership, equity, and physician governance.

Leads applied research programs in innovation, implementation science, digital health, and AI-enabled healthcare. Provides scientific oversight for multidisciplinary studies, clinical trials, pragmatic research, analytics, program evaluation, grant development, and scientific writing. Collaborates with clinical and operational stakeholders, mentors trainees, manages research resources and external relationships, and ensures methodological rigor, productivity, and responsible data stewardship. The role focuses on translational, non-laboratory research using health system data and clinical workflows.

Serve as a client-facing Tier 2 SOC Analyst supporting detection strategy, alert tuning, threat detection, and attack surface reduction. Responsibilities include reducing alert fatigue, managing MDR provider feedback loops, implementing SentinelOne rules, mapping detections to security frameworks, coordinating remediation, prioritizing vulnerabilities, reporting metrics, and improving identity and privileged-account controls. The role requires AI tools, SIEM and EDR experience, knowledge of attacker tactics, and strong technical communication.

Owns product strategy, roadmap, and execution for AI-powered experiences serving home service professionals. Responsibilities include researching workflows, defining requirements, shaping model behavior and user experiences, prioritizing roadmaps, establishing product and AI performance metrics, coordinating launches, and improving products through customer feedback and analytics. The role partners closely with Engineering, Design, Data, Marketing, Sales, Customer Success, Operations, and AI platform teams.

Conduct cyber discovery and sustainment analysis of Advanced Persistent Threats using SIGINT, AMOD, stored communications, passive resources, raw traffic metadata, and attribution techniques. Perform malware triage and characterize zero-day CNE campaigns. Apply machine learning and artificial intelligence to focused discovery efforts. The role requires substantial computer or information systems analysis experience, a relevant degree or equivalent experience, U.S. citizenship, and an active TS/SCI clearance with an agency-appropriate polygraph.

Leads AND Digital’s Data and AI practice in the US by advising C-suite clients, shaping enterprise AI solutions, overseeing architecture and delivery quality, driving go-to-market growth, developing partner relationships, and mentoring distributed engineering teams. The role combines hands-on technical leadership across AWS, Snowflake, and modern data platforms with commercial responsibilities including presales, propositions, thought leadership, and revenue generation.

Own end-to-end AI transformation engagements for financial-services enterprises, from executive vision and use-case discovery through roadmapping, implementation, adoption, and value realization. Lead transformation offices, executive workshops, business cases, delivery governance, and cross-functional deployments. Address regulatory, data, governance, and change-management barriers while developing reusable AI transformation frameworks, playbooks, maturity models, and value assessment tools.

Leads a customer support team by hiring, coaching, training, managing performance, balancing workloads, and ensuring service levels. Monitors KPIs, reports, and dashboards to improve resource allocation, efficiency, and customer satisfaction. Handles escalated customer issues, supports sales onboarding, maintains procedures, and partners cross-functionally with sales, marketing, finance, operations, and HR to improve customer experience and processes.

The Strategic Initiatives Lead partners with the Chief of Staff to solve high-priority business problems across Growth and go-to-market functions. Responsibilities include identifying scalable pipeline channels, building AI-enabled demand-generation workflows with tools such as Clay and n8n, analyzing data, executing initiatives end to end, developing recommendations, and documenting successful processes into repeatable playbooks.

Lead complex, multi-workstream SaaS implementations from contract to validated outcomes. Own scope, timelines, budget, risk, and governance; align executives; coordinate Solution Architecture, Product, and Engineering; develop reusable playbooks; mentor TPMs; and ensure technically sound integrations without serving as the primary engineer.

Conduct applied AI and machine learning research for aerial, maritime, and underwater autonomous systems. Develop computer vision, multimodal perception, sensor fusion, reinforcement learning, and uncertainty-aware models; integrate them with physical platforms and autonomy stacks; run experiments; and build evaluation pipelines and operator-facing tools. The role also involves technical reporting, proposal development, stakeholder briefings, student mentoring, and collaboration with faculty, defense partners, and Navy program stakeholders.

Leads enterprise architecture for data, analytics, and AI/ML platforms. Defines cloud, Lakehouse, streaming, governance, integration, and machine-learning architecture standards; guides modernization, proof of concepts, platform scalability, security, and cost optimization. Partners with executives, product owners, cybersecurity, governance, and engineering teams while leading design reviews, architecture forums, and technical programs. Requires deep experience with Databricks, cloud-native data platforms, distributed systems, data governance, and enterprise-scale architecture.

Leads the global sales operations infrastructure, including GTM planning, territory and quota design, forecasting, pipeline accountability, renewals, expansion, partner and BDR programs, and international growth. Builds and manages a global operations team, automates sales workflows, develops AI-enabled GTM strategies, and presents data-backed recommendations to executive leadership while partnering across Sales, Marketing, Customer Experience, Finance, and GTM Engineering.