Top Artificial Intelligence Jobs

Lead design, deployment, and support of agentic AI solutions and LLM-based workflows integrated with Oracle SCM/PLM. Build prompt orchestration, RAG, and agent frameworks, manage integrations (REST/SOAP), enforce data governance/security, monitor agent performance, and drive cross-functional adoption, documentation, and continuous improvement.

The role involves building AI tools and coding agents, fine-tuning LLMs, and collaborating on product features to support CUDA developers at NVIDIA.

Lead a cross-functional team to design, prototype and deploy AI-powered solutions that improve sales performance, efficiency and customer experience. Prioritise opportunities, deliver rapid prototypes using Evo Builder and Coworker Creator, align stakeholders, and drive measurable GTM impact through change and continuous improvement.

Design, implement, and scale enterprise-grade LLM and agent-based GenAI systems (using ADK, LangChain). Build multi-agent orchestration, tool chaining, real-time/asynchronous pipelines, API integrations, guardrails, observability, and partner with Risk/Compliance for MRM validation. Lead delivery, mentorship, and reusable AI engineering standards for production deployments.

Design, build, deploy, and operate AI-enabled backend services and workflows for risk decisioning. Combine LLMs, retrieval, tool use, and deterministic logic with robust monitoring, fallback strategies, and production readiness. Partner cross-functionally to define quality bars, evaluate AI outputs, and improve reliability, scalability, security, and cost efficiency.

Design, implement, and maintain AI-driven workflow automations using Microsoft Power Automate and approved AI tools. Discover and document business processes, translate needs into requirements, coordinate custom NEXUS development with software teams, deliver training and documentation, monitor adoption and performance, and ensure Responsible AI and compliance practices across ISAT, CEAS, and Tomarco business units.

Lead technical strategy with channel partners across ASEAN to build repeatable Microsoft Cloud and AI Workforce offerings (Copilot, Power Platform, Agents). Drive architecture design, workshops, POCs, offer development, partner enablement, and co-sell execution to convert technical capability into scalable revenue and customer outcomes.

Manage strategic accounts (Ford, Rivian) for NVIDIA automotive products, drive design wins in autonomous driving and cockpit systems, build relationships with R&D and procurement, understand customer architectures and competition, coordinate internal teams, and identify vehicle platforms and key Tier 1 contacts to grow revenue.

Manage and grow the Tesla account for NVIDIA's automotive products by driving design wins and revenue in autonomous driving and cockpit systems. Build strategic relationships with OEMs, Tier 1s, R&D and procurement; understand customer architectures and competition; evangelize deep learning solutions; and coordinate internal teams to deliver customer-focused solutions.

Build and ship LLM- and agent-powered product experiences for North, designing interfaces, evals, observability, and feedback loops to improve reliability and user outcomes. Collaborate with modelling, product, design, and customers to turn failures and feedback into measurable product and model improvements.

Sell advanced visualization, AI, and cardiopulmonary imaging solutions across the Midwest territory. Build strategic sales plans, grow accounts, deliver clinical/technical presentations, support purchasing decisions, forecast sales, maintain CRM records, and collaborate with cross-functional teams to drive adoption and ensure compliance with company policies and quality standards. Travel ~50%.

Lead scoping, design, development, testing, and deployment of AI/ML solutions for prosecutor workflows. Manage teams, on-prem and cloud AI infrastructure, LLM fine-tuning, RAG pipelines, guardrails, auditability, and governance while liaising with stakeholders and vendors.

Founding Full-Stack AI Engineer to architect, build, and scale an enterprise digital account manager. Own end-to-end features, build integrations and data ontology mapping, develop intuitive UIs, and design agentic LLM solutions (memory, RL). Work directly with founders and customers to iterate rapidly and deliver enterprise-grade, scalable AI products onsite in San Francisco.

Lead a regulator-facing data and AI modernization program with end-to-end delivery oversight: stakeholder engagement, financial and PMO management, Agile execution, resource planning, risk and quality oversight, and executive reporting across technical and business workstreams.

Design, build, and maintain production-grade agent harnesses and platform capabilities for generative AI applications. Lead architecture and delivery, improve CI/CD, testing, observability, and security, mentor engineers, and collaborate with stakeholders to enable scalable, enterprise-grade agent runtimes and integrations.

Serve as the finance business partner for a firm business line: provide strategic financial advice, build models, lead reporting and planning, analyze performance drivers, support investment cases, create executive/board presentations, champion automation and AI, and collaborate cross-functionally with Finance, Accounting, and Corporate FP&A.

Lead delivery of Generative AI and AI-enabled solutions: gather requirements, design and build LLM-based applications, APIs, integrations, and workflow automation. Manage end-to-end project delivery, enforce governance/security/Responsible AI, monitor KPIs, and coordinate cross-functional teams to drive adoption and business outcomes.

Lead end-to-end design, development, and delivery of enterprise Generative AI and ML solutions. Architect scalable LLM, RAG, and agent-based systems, drive technical decisions, implement production-ready MLOps/CI-CD, and mentor engineers. Collaborate with product and business stakeholders, ensure monitoring, security, and operational support, and evaluate emerging AI technologies to improve delivery.

Lead strategy and build 0->1 AI products that streamline complex healthcare workflows across providers, pharmacies, patients, and pharma partners. Own roadmap, requirements, metrics, and product performance; partner with engineering, data, clinical, and commercial teams to launch and iterate AI-enabled solutions that drive adoption and measurable business and patient outcomes.

Lead the architecture, build, and deployment of AI-driven automation and intelligent systems to solve security, compliance, and risk challenges. Develop real-time intelligence, workflow automation, and risk-based decision-making tools, and engage customers and partners to refine and deploy production-grade solutions.

Design and implement analytic methods to extract meaning from large, messy NSA/CSS datasets. Build and evaluate models, manage and curate data, translate mission needs into technical requirements, and communicate technical conclusions to non-technical stakeholders while accounting for collection and processing constraints.

Manage a portfolio of key West Coast accounts to drive revenue growth by identifying new opportunities, building C‑level relationships, applying consultative enterprise sales, coordinating cross-functional teams and partners, maintaining CRM hygiene, and supporting handover to Customer Success for implementation and retention.

Design and deliver secure, compliant Azure and hybrid cloud infrastructure and AI-ready platforms for federal customers. Lead architecture, proofs of concept, governance, identity, networking, resiliency, and operational controls. Advise customers, enable partners, mentor peers, and drive cloud adoption while ensuring compliance with federal security requirements.

Build and own an internal AI-powered recruiting pipeline: end-to-end LLM-based sourcing, screening, AI interviews, evaluation logic, and deep integrations with ATS and scheduling to automate hiring workflows.

Lead the AI platform that enables all products: define runtime/orchestration, platform contracts, model lifecycle, inference performance, safety/compliance, evaluation, and voice/multimodal integration. Set technical direction, mentor PMs, partner with engineering to scale to millions, and prioritize platform investments while enforcing governance and reliability.