Top Artificial Intelligence Jobs

Develop C#/.NET APIs for an enterprise data platform, perform gap analysis, and build REST integrations using microservices and event-driven architecture. Implement CI/CD, containerization, and API management. In a later phase, integrate LLMs, build RAG and AI APIs, use orchestration frameworks, tune prompts and model parameters, and implement AI gateway capabilities such as token limits and model routing.

Lead a hands-on platform engineering function spanning full-stack product development, real-time Kafka and ClickHouse data/ML pipelines, cloud infrastructure, DevOps, security, and reliability. Own React, Node.js, and MongoDB applications; Terraform, Kubernetes, AWS/GCP, Docker, and GitHub Actions; production observability and incident response; and SOC 2 readiness. Establish AI-assisted engineering workflows using tools such as Claude Code and Cursor while replacing vendor-built infrastructure with durable internal automation.

Designs, deploys, and operates production machine learning systems for identity resolution, scoring, deliverability, and personalization. Responsibilities include feature engineering, model training, real-time inference, graph database integration, monitoring, drift detection, retraining, low-latency APIs, and scalable data processing. The role also contributes to MLOps standards, GPU acceleration, and ML architecture while partnering with platform engineering.

Build and deploy production AI and process automation solutions for Corporate Services. Responsibilities include developing agentic workflows, LLM-powered analytics, document intelligence pipelines, RAG systems, copilots, and end-to-end workflow automation. The role partners with business stakeholders to scope, build, deploy, monitor, and iterate products while applying strong engineering practices, reusable patterns, testing, observability, security, and enterprise deployment standards.

Designs, administers, and improves Microsoft 365 and Power Platform environments, including Exchange, Teams, SharePoint, OneDrive, Copilot, Intune, Defender, and Purview. Leads platform projects from requirements through adoption and support, builds Power Platform automations and AI-enabled solutions, develops integrations using PowerShell, Microsoft Graph, Azure, and APIs, and partners with security, IAM, compliance, and AI teams to ensure effective governance, security, and operational readiness.

Secure and operate AI platforms, gateways, agents, and tool integrations across their lifecycle. Build security automation, privileged access controls, network and endpoint protections, logging and telemetry pipelines, SIEM integrations, dashboards, alerts, and monitoring. Review integrations for security risks, enforce authentication, authorization, guardrails, and usage governance, and support firewall, SASE/ZTNA, WAF, identity, and infrastructure security engineering.

Build and operate enterprise data and AI systems, including ELT, streaming, semantic, embedding, indexing, vector search, and RAG pipelines. Develop safe tool interfaces for agents, implement data products and contracts, and establish quality, observability, evaluation, and governance practices for AI workloads. Collaborate with architects, data scientists, AI engineers, governance teams, and domain engineers to productionize AI use cases and reusable platform patterns.

Build and maintain AI-assisted workflows, automations, integrations, internal tools, reports, and dashboards. Investigate failures, improve data reliability, monitor systems, document processes, support access and recovery, and train team members. The role requires hands-on ownership from problem definition through implementation and ongoing support, with careful attention to accuracy, privacy, security, and operational reliability.

Designs, develops, deploys, and operates AI capabilities for enterprise and facilities-management platforms. Responsibilities include building intelligent assistants, RAG and semantic search solutions, document intelligence workflows, AI APIs, data pipelines, prompt and retrieval strategies, and evaluation frameworks. The role also covers Azure cloud deployment, CI/CD, MLOps, monitoring, security, governance, and responsible AI practices.

Supports Deutsche Bank’s Wealth Management Transformation team on Agentic AI and digital innovation initiatives. Responsibilities include gathering and analyzing business requirements, evaluating AI use cases, mapping processes, identifying automation opportunities, preparing documentation and presentations, supporting testing and rollouts, and analyzing business outcomes. The intern collaborates with stakeholders, product owners, and technology teams while developing business analysis, project management, and digital transformation skills.

Manage executive client relationships and account planning for Gartner Enterprise IT Leaders. Advise senior technology, procurement, sourcing, vendor management, and finance leaders on strategic priorities, organizational design, initiatives, metrics, and technology trends. Develop customized engagement plans, deliver executive briefings, workshops, and webinars, and support the full member lifecycle from pre-sale through renewal. Contribute to retention, sales growth, relationship management, and actionable business and technical advice.

Leads strategic finance for Sony Pictures’ global YouTube and social platforms portfolio. Responsibilities include annual planning, forecasting, long-range planning, executive reporting, investment and portfolio analysis, monetization modeling, KPI dashboards, scenario planning, governance, cost optimization, and cross-functional decision support. The role partners with senior executives, leads finance-team development, and applies AI, automation, and advanced analytics to improve forecasting and business performance.

Leads KI’s application development, AI, data, analytics, and enterprise architecture functions. The Director establishes AI strategy and governance, develops technology roadmaps, advances data and reporting capabilities, guides software teams, identifies automation opportunities, partners with business leaders, manages budgets and technology partnerships, and develops organizational talent.

Leads AMER technical customer support for Navico Group brands, developing service strategies, managing team performance, resolving complex escalations, and improving customer satisfaction. Uses analytics, KPIs, customer feedback, automation, and AI to enhance service delivery. Partners with Service, Sales, Product Management, Quality, and other teams on product and process improvements. Mentors direct reports and oversees scalable support systems across locations. Requires technical troubleshooting expertise, leadership experience, and familiarity with marine electronics and CRM tools.

Own end-to-end analytics engineering for AI and developer-experience telemetry, including instrumentation, production pipelines, governed metrics, monitoring, executive dashboards, and analysis. Define and validate new measures of AI productivity and ROI, communicate findings to senior stakeholders, and recommend improvements to tooling, processes, and investment. Collaborate with data engineering, applied AI, and data science teams while using AI coding agents to build and maintain pipelines and reporting.

Defines architecture and technical strategy for evaluating LLM, RAG, and agentic AI systems across the product lifecycle. Designs evaluation frameworks, metrics, datasets, dashboards, release gates, monitoring, and experimentation workflows. Analyzes model behavior, retrieval quality, failure modes, safety, and product impact, then guides improvements across prompts, tools, orchestration, search, UX, and code. Partners with engineering, applied science, data science, and product teams; leads cross-functional initiatives and mentors technical staff.

Designs and leads enterprise AI infrastructure, including large-scale GPU clusters, Kubernetes and HPC platforms, high-speed network fabrics, infrastructure-as-code, GitOps, workload scheduling, observability, and SRE automation. The role establishes architecture, optimizes systems performance, leads incident response and recovery, manages platform governance, and mentors engineers while collaborating with AI researchers, hardware teams, and technology partners.

Designs and delivers Finance BI dashboards, data models, reports, and self-service analytics. Translates Finance requirements into technical specifications, investigates data discrepancies across SAP and other enterprise systems, performs SQL-based reconciliation and root-cause analysis, and improves reporting performance and reliability. Leads testing, governance, controls, and stakeholder sign-off while evaluating automation and AI-assisted analytics opportunities.

Designs and deploys AI/ML analytics solutions for Finance, including forecasting, anomaly detection, classification, and NLP. Builds Snowflake data models and pipelines, debugs enterprise data warehouse flows, integrates LLMs and generative AI, and establishes model monitoring, versioning, and governance. Partners with finance stakeholders to translate business needs into production-ready intelligent insights.

Lead systems engineering adoption within a Digital Engineering and AI council and embedded program teams. Define standards, roadmaps, metrics, and reusable practices; coach engineers in model-based systems thinking and digital workflows; connect requirements, architecture, analysis, design, and verification evidence; pilot AI-supported techniques; track adoption; and transition teams to sustained ownership while providing on-call expertise.

Leads systems engineering strategy and adoption within a Digital Engineering and AI council. Develops standards, roadmaps, metrics, and reusable practices while embedding model-based systems engineering and AI-supported workflows into program teams. Coaches engineers, integrates requirements through verification evidence, tracks adoption, and transitions teams to independent ownership. Requires cross-functional engineering leadership, digital engineering experience, a STEM bachelor's degree, U.S. citizenship, and eligibility for a Secret clearance.

Identify bottlenecks in professional creative workflows and turn them into AI-powered, end-to-end workflows and polished interactive prototypes. Research user needs, design intuitive experiences, define quality standards, validate hypotheses, and collaborate with product, model, and engineering teams to ship successful concepts. The role requires professional creative production knowledge, strong product taste, AI coding and prototyping ability, and experience using tools such as Figma, model APIs, and agent frameworks.

Build AI-powered features and products for clinical documentation and medical coding. Develop LLM-driven agentic systems, APIs, services, and production infrastructure across healthcare revenue cycle workflows. Create evaluation frameworks and experimentation loops using statistical and data-driven methods to ensure reliability, auditability, and alignment with coding guidelines and user feedback. Collaborate with product, design, machine learning, clinical, and revenue cycle experts to deliver high-impact SaaS solutions.

Own Chai Discovery’s brand, messaging, identity, website, events, and marketing systems as its first marketing hire. Build a compelling presence for pharma executives, scientists, AI researchers, and prospective employees. Set creative direction, manage agencies and vendors, support founders and researchers with communications platforms, lead conference and partner-event experiences, and create a repeatable marketing playbook while translating complex technical and scientific work into accessible stories.

Lead infrastructure engineering for GenAI-powered agents, AWS cloud cost optimization, and FinOps automation. Architect runbooks, Policy as Code, and resilient infrastructure solutions while guiding teams on cost-effective design. Own FinOps AI applications, dashboards, documentation, compliance, and auditability. Collaborate across platforms to modernize technology processes, validate AI recommendations, and improve cloud efficiency, performance, security, and governance.