Top Artificial Intelligence Jobs

Brings up and optimizes foundation models on SambaNova’s AI platform. Profiles performance across compiler, runtime, and hardware layers; identifies bottlenecks; applies quantization, kernel fusion, scheduling, and memory optimizations; benchmarks inference throughput and latency; and collaborates with machine learning, compiler, runtime, and hardware teams to deliver product improvements.

Designs, develops, deploys, and supports enterprise AI solutions across Northern Trust’s Digital Coworkers and Generative AI Foundation Platform. Responsibilities include full-stack application and API development, Azure cloud engineering, Terraform infrastructure, CI/CD, LLM and RAG integrations, AI agents, workflow automation, monitoring, governance, and production support. The role partners with engineering, architecture, security, product, and business teams to deliver scalable, secure, governed AI capabilities in a regulated financial-services environment.

Own the architecture, deployment, and reliability of CreateOS’s agentic AI platform. Build orchestration, RAG, memory, routing, guardrails, evaluation, and observability systems; integrate LLMs into production features; and ship full-stack AI applications. Partner with business stakeholders, define technical requirements, maintain production engineering standards, guide architecture, mentor engineers, and establish scalable development patterns for AI systems serving users at scale.

Lead Anthropic’s US AI regulatory legal work, including applicability analysis, compliance readiness, regulatory deliverables, agency engagement, rulemaking submissions, and enforcement support. Counsel cross-functional legal, policy, safety, security, research, product, and business teams on emerging AI requirements. Track US and international regulatory developments, design scalable compliance programs, and contribute to global frontier AI compliance strategy, including relevant EU AI Act work.

Build and lead Anthropic’s Applied AI Security team from the ground up. Hire and develop customer-facing security architects, prioritize customer segments and account coverage, partner with sales on enterprise security deals, and guide customers through evaluations and production deployments. Develop security playbooks and responsible AI practices for application security, penetration testing, alert triage, vulnerability management, and threat intelligence. Maintain strategic customer relationships while collaborating with engineering, product, legal, trust, and ecosystem partners.

Build and optimize C++ or Rust services running on vehicle compute across Linux, Android, and QNX. Work on telemetry, high-throughput vehicle data uploads, connected features, and on-device ML inference for speech and wake-word systems. Instrument, benchmark, debug, and performance-test software on constrained automotive hardware, while contributing design documents, code reviews, and field troubleshooting.

Own go-to-market for an early-stage AI coworker startup, including positioning, ICP validation, pricing, outbound sales, demand generation, design partners, and early revenue. The role involves closing initial customers, translating customer feedback into product direction, establishing the GTM stack and metrics, and later hiring and leading the GTM team. This is a hands-on founding role working closely with the founder and engineers.

Leads Salesforce’s AI Labs Customer Success organization, managing enterprise CSM teams and a portfolio of strategic accounts. Owns customer retention, adoption, expansion, renewals, executive relationships, business outcomes, and operational metrics. Hires, coaches, and develops talent while partnering with Sales, Product, Support, Alliances, and strategic partners. Drives scalable customer success methodologies, AI-enabled workflows, and cross-functional strategies for digital and AI transformation.

Conduct AI research with Salesforce scientists and engineers, exploring enterprise AI directions and building models, agents, and production-oriented prototypes. Interns may publish at leading conferences, investigate agentic AI, multimodal systems, speech intelligence, reasoning, reinforcement learning, and model post-training, while translating research into customer-impacting products. The role involves collaborating across research, product, engineering, and go-to-market teams and requires strong technical independence, problem-solving, and communication skills.

Design, develop, modify, diagnose, prototype, and deploy machine learning, deep learning, image processing, and computer vision algorithms. Train and deploy production ML/AI models, create model architectures, modify loss functions, and contribute independently and collaboratively to semiconductor inspection technology. Strong communication and problem-solving skills are required.

Provide hands-on creative support for customers using Hightouch Ad Studio. Improve AI-generated images, videos, ads, and other marketing assets through prompt refinement, editing, style and context adjustments, and troubleshooting. Create customer guides and video walkthroughs, communicate model behavior to Forward Deployed Creatives and product teams, and identify issues requiring broader support. The role requires strong static and motion design judgment, AI prompting expertise, marketing fundamentals, and the ability to handle varied creative requests quickly.

Designs semantic, knowledge, metrics, and governance layers that enable AI agents to use trusted data. Responsibilities include developing ontologies, business glossaries, search indexes, entitlement frameworks, lineage standards, and data readiness assessments. The role translates business rules into scalable models, implements event-driven architectures, and supports semantic search, vector databases, and RAG systems. It also leads SME workshops and provides architectural recommendations to senior stakeholders.

Evaluate AI coding agents such as Codex, Claude Code, and Cursor for reasoning quality, engineering judgment, explanations, usefulness, and user trust. Provide rigorous, opinionated feedback distinguishing response-quality levels and help define standards for excellent AI-assisted development. This contract role requires staff- or principal-level engineering experience and familiarity with modern AI development workflows.

Own and advance Wonderlic’s AI-powered Jobs Engine, using production machine learning and NLP to analyze labor-market data and infer job characteristics at scale. Partner with product, engineering, and I-O psychology teams to integrate responsible AI into assessment and workforce solutions. Apply fairness, explainability, legal defensibility, and rigorous evaluation practices to employment-related AI systems, including generative AI outputs and assessment interpretation.

Build and productionize AI agent capabilities for revenue workflows. Responsibilities include designing agent harnesses, execution loops, tool interfaces, context and memory systems; shipping end-to-end AI features; creating evaluations and analyzing execution traces; improving reliability, latency, cost, and error recovery; experimenting with models, prompting, retrieval, and orchestration; and developing reusable AI engineering foundations.

Develop and execute enterprise sales and go-to-market strategy for emerging AI agent products. Build executive relationships, identify use cases, manage sales from discovery through closing, and partner with product and engineering on positioning, packaging, pricing, pilots, and product requirements. Establish repeatable processes for converting experimentation into production deployments while providing market feedback and shaping a new product category.

Own the strategy, roadmap, and lifecycle for Cisco’s AI-driven SASE platform. Design agentic workflows that unify network and security operations, integrate AI models, and improve automation and investigation speed. Coordinate engineering, data science, design, marketing, business development, and support teams from ideation through commercialization. Define product metrics, communicate value propositions, drive customer and partner adoption, and oversee platform enhancements and releases.

Build and deploy AI automations, agents, dashboards, data pipelines, and internal tools using Claude, Microsoft 365, Python, and JavaScript. Prototype solutions such as intelligence scrapers and board-report generators, evaluate AI models and frameworks, and provide recommendations to the investment team. The role involves direct collaboration with a founding partner, user feedback, and in-office work in Manhattan Beach at least three days weekly.

Build and deploy autonomous, multi-agent AI systems using LangChain, LangGraph, AutoGen, MCP, and A2A. Develop RAG pipelines with Knowledge Graphs, fine-tune language models for edge deployment, and create evaluation frameworks for reliability, safety, and performance. The role also involves production ML engineering, cloud architecture across AWS and Azure, microservices, observability, and collaboration in classified environments.

Lead technical product marketing for Plaud’s software and AI portfolio. Translate product architecture and capabilities into positioning, messaging, content, enablement, and launch strategies. Own go-to-market architecture, coordinate cross-functional teams, support regional activation, and use customer, market, and launch insights to improve adoption and product narratives. The role requires strong technical fluency, excellent writing, project leadership, and experience operating independently in fast-changing environments.

Lead the company-wide strategy and adoption of AI and emerging technologies. Build internal tools, scripts, and workflow automations; evaluate software and vendors; establish responsible AI, data security, and governance practices; provide technical support and training; and partner with leadership on technology priorities, budgets, roadmaps, and ROI across engineering and operations.

Lead the vision, strategy, and roadmap for AI-native client products, internal tools, data products, and enterprise integrations. Partner with executives, engineering, and data science to evaluate models, data quality, infrastructure, cost, latency, trust, and scalability. Define AI product opportunities, business cases, data requirements, quality standards, and commercial strategies while aligning legal, privacy, trust, and safety stakeholders.

Own the roadmap, backlog, and delivery of data products and an internal data marketplace. Translate stakeholder needs into prioritized requirements, partner with engineering and governance teams, launch reusable and trusted data products, and measure adoption, quality, and business impact. The role also supports AI-enabled data access, external product readiness, documentation, certification, and ongoing product operations.

Own Monad’s AI and compute ecosystem business development strategy. Source and activate AI founders, venture firms, compute providers, protocols, liquidity providers, and trading partners. Build relationships, structure and close commercial collaborations, drive agentic payment and compute-market integrations, and coordinate technical, ecosystem, legal, and communications teams. Track launches, users, payments, liquidity, and transaction volume while establishing Monad as a settlement layer for AI and compute products.

Design, develop, test, and deploy AI/ML services and agentic workflows for rugged tactical networking and computing systems. Translate business needs into technical requirements, collaborate with technical owners, and build scalable applications using Python, Linux, cloud-native infrastructure, AI frameworks, databases, observability tools, and CI/CD pipelines. The role supports mission-critical government, defense, and intelligence applications.