Top Artificial Intelligence Jobs

Lead the product vision and roadmap for an agentic AI platform, ship autonomous agents for fintech workflows, drive LLM fine-tuning strategy, partner with Engineering/Design/Data Science, and ensure governance, safety, and compliance for production agents.

Lead end-to-end enterprise AI adoption engagements: assess readiness, prioritize use cases, design adoption roadmaps and governance, run enablement and champion programs, measure value and ROI, set responsible-AI guardrails, and scale repeatable playbooks while advising executives and coaching teams.

Lead development and commercialization of Cloud Data solutions: design cloud data architectures, lead migrations and ETL/ELT, operationalize AI across clouds, support strategic sales pursuits, enable and train solution architects, secure partner co-investment, and provide steering‑committee oversight to mitigate delivery risk and drive practice growth.

Lead and scale engineering teams to design, build, and operate enterprise-scale AI-powered software and platforms. Define technical strategy, establish engineering best practices and architecture governance, partner with Product and Security, deliver secure, resilient cloud-native solutions, and recruit and develop engineering leadership to drive measurable business value through Generative AI and agentic technologies.

Own the networking vision and roadmap for k0rdent AI, defining underlay/overlay fabrics, RDMA, DNS/IPAM, network automation, and DPU/SmartNIC integration. Translate customer and engineering requirements into priorities, track emerging interconnect standards, and support positioning, field engagements, and reference architectures.

Design and build a secure, scalable platform for AI-enabled applications to integrate with Zipline production systems. Implement reusable APIs, gateways, middleware, and guardrails (auth, rate limits, observability) while partnering with AI engineers and service teams to ensure reliability, ownership, and safe production deployments.

Develop and deploy AI/ML methods (including LLMs/agentic AI) for tuning, diagnosis, control, and automation of particle accelerators. Test methods experimentally on the APS injector and upgraded storage ring, support operator decision-making, automate workflows, and analyze beam and system data.

Lead enterprise AI and digital transformation strategy across functions and business segments. Develop AI vision, prioritize and manage product lifecycles, drive use-case development and ROI analysis, oversee adoption and change management, ensure AI risk/compliance governance, and measure performance against KPIs.

Lead AI-focused business transformation for energy, transportation, and industrial clients: identify high-impact AI use cases, build roadmaps, drive change management and governance, coordinate with technical teams to move pilots to production, measure adoption and impact, and mentor junior consultants.

Lead strategy and delivery for AI-enabled transformation across energy, transportation, and industrial clients. Identify high-impact AI use cases, build roadmaps, drive change management and governance, coordinate with technical teams, measure adoption and business impact, and mentor junior consultants.

Build and operate regulator-grade, production AI-enabled full‑stack applications: real-time audit dashboards, CAAT/continuous-monitoring surfaces, and agentic human-in-the-loop apps. Own end-to-end stack from data modeling and APIs to React/Next.js UIs, ensure responsible-AI practices, data protection, audit trails, and drive adoption with non-technical auditors.

Lead enterprise AI strategy, prioritize high-value use cases, and oversee end-to-end model development, MLOps, governance, deployment, and adoption. Build and mentor AI teams, partner with technology and business units, manage vendors and budgets, and measure business impact while ensuring responsible AI practices and stakeholder alignment.

Lead AI-driven transformation of controllership and accounting processes: identify optimization opportunities, design AI-enabled workflows, develop pilots, partner with IT and finance SMEs, implement solutions, define metrics, ensure controls and change management, and build AI literacy across Controllership.

Own full sales and partnership cycle to bring voice AI to mobile service robots: engage senior robotics decision-makers, qualify and prioritize opportunities, close deals, and shape the commercial playbook while operating autonomously within a small technical team.

Lead technical engagements with robotics customers to design and integrate voice AI into mobile robots, own POCs and technical evaluations, clear deployment roadblocks, collaborate with sales/product/services, and feed customer learnings into the product. Travel across Europe for onsite evaluations (20–30%).

Senior technology executive responsible for defining and executing enterprise Data & AI strategy. Lead Data Engineering, Analytics, Architecture, Governance, Data Products, and AI/ML to modernize data platforms, ensure compliance (HIPAA), operationalize AI/ML, and align investments with organizational priorities. Oversee budgets, vendor relationships, and cross-functional partnerships to deliver data-driven products and responsible AI at scale.

Lead technical design and delivery of enterprise-facing AI products end-to-end. Partner with product, design, sales, and research to turn enterprise workflows into shipped features, set architecture and standards, mentor engineers, and build extensible integrations, plugins, and multi-step agents for organizational use.

Lead and operate enterprise Azure and Microsoft 365 platforms, manage hybrid identity (Entra ID/AD), deliver and govern AI solutions (Azure OpenAI, Azure ML, Copilot), provide L2/3 support, secure and govern cloud resources, manage on‑prem infrastructure, and drive vendor, project, and stakeholder engagement to scale AI initiatives.

Build and maintain cloud infrastructure and observability for scalable systems. Monitor, troubleshoot, patch, and automate operations using IaC, CI/CD, Kubernetes, and AI-driven automation. Manage backups, disaster recovery, log pipelines, databases, and message streaming. Collaborate with engineering, security, and business teams to improve reliability, incident response, and infrastructure lifecycle (including Terraform state cleanup and decommissioning).

Lead development and industrialization of enterprise AI/ML solutions (recommendation engines, forecasting) for Commercial, Marketing, and Medical Affairs. Translate ambiguous business problems into analytical roadmaps, drive end-to-end productization, partner with cross-functional teams, and communicate technical insights to influence strategy and operational actions.

Lead and operate technical support and escalation for Rosalind and life sciences customers. Own complex cases from intake to resolution, diagnose product and configuration issues across ChatGPT, Codex, and the OpenAI API, build bioscience-aware intake flows, playbooks, and knowledge, coordinate cross-functional escalations, and drive durable fixes, automation, and product improvements while maintaining boundaries around scientific consultation.

Lead TiDB's AI ecosystem partnership strategy across North America and EMEA, building product-level integrations with LLMs, cloud providers, and AI platforms. Drive joint solution blueprints, reference architectures, co-innovation, developer enablement, and measure ecosystem-influenced pipeline while collaborating with Product, Engineering, Marketing, and Sales.

Lead data management and quality efforts, consult with stakeholders and vendors, design processes and solutions, perform root-cause analysis of complex data errors, implement improvements, integrate technologies, validate deliverables, and present recommendations to senior management to enable AI-ready data and BI solutions.

Own full-cycle recruiting for FDE and FDX technical roles across the US, source passive AI/ML and software engineering talent, build talent communities and events, manage pipelines and offers, and partner on workforce planning and candidate experience.

Embed with customers to learn and rebuild critical business functions, then design and ship production GenAI/LLM systems on AWS. Own delivery end-to-end: operator immersion, design, implementation, evaluation, and stakeholder alignment while remaining hands-on in code and cloud-native ops.