Top Artificial Intelligence Jobs

Lead engineering for production-grade agentic AI and LLM platforms. Design AWS cloud-native services, RAG solutions, vector storage, agent memory, APIs, and microservices. Establish MLOps, monitoring, governance, security, observability, and responsible AI practices. Provide technical direction, make architecture decisions, review code, mentor engineers, and drive adoption of AI-assisted development standards across teams in a regulated enterprise environment.

Conducts research on algorithms for large language models and agentic AI systems, improving learning efficiency, inference performance, accuracy, latency, and compute cost. Develops theoretical foundations, implements performant software, validates methods at scale, solves problems for internal teams, publishes findings, presents research, and contributes to intellectual property protection.

Design, develop, test, deploy, and support production AI systems, including foundation-model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI training and inference for scalability, latency, throughput, hardware utilization, and cost. Shape the technical vision and roadmap for foundational AI platforms while partnering with engineers, researchers, program managers, and product leaders. Mentor engineering teams and influence senior cross-functional stakeholders.

Designs, develops, tests, deploys, and supports foundational AI systems, including model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. Develops optimization techniques to improve scalability, latency, throughput, hardware utilization, and cost. Partners with engineering, research, product, and program teams; contributes to technical vision and roadmaps; and mentors teams while applying emerging AI research to production systems.

Leads FP&A and strategic finance for enterprise AI initiatives, including forecasting, budgeting, financial analysis, funding prioritization, roadmap planning, and executive reporting. Manages and develops a finance team, partners with product, engineering, strategy, and finance leaders, identifies cost drivers and business opportunities, and recommends actions based on analytical insights. Drives projects, process improvements, automation, and cross-functional decision-making.

Own and negotiate Firecrawl’s commercial agreements, including enterprise contracts, data licenses, vendor agreements, NDAs, and partnerships. Advise sales, business development, product, and engineering on data rights, privacy, security, intellectual property, indemnification, and liability. Build legal templates, playbooks, fallback positions, and approval processes while supporting compliance initiatives. Operate autonomously, escalate novel issues appropriately, and provide practical business-focused legal guidance in a fast-moving AI infrastructure company.

Define Order.co’s company-wide data and applied AI architecture, standards, governance, and investment strategy. Build production AI systems spanning data platforms, retrieval, model serving, evaluation, guardrails, and agentic workflows. Partner with the Head of Data, product, engineering, and operations leaders to fund and deliver initiatives that improve company KPIs. Mentor senior contributors, establish reusable engineering patterns, and ensure AI systems meet security, reliability, observability, privacy, and operational requirements.

Designs, deploys, maintains, and troubleshoots HPE NonStop payment infrastructure, secure key managers, Etinet servers, and related subsystems. Uses AIOps and AI-assisted practices for incident triage, anomaly detection, automation, documentation, and reliability improvements. Partners with SRE, observability, and cybersecurity teams to govern AI-enabled monitoring, maintain auditability, execute upgrades, and produce operational knowledge such as runbooks and troubleshooting guides.

Leads the engineering organization for a firm-wide software dependency risk platform. Responsibilities include hiring and managing engineers and engineering managers, owning platform architecture and roadmap on AWS and Java, building data ingestion and dependency graph capabilities, establishing AI-first development practices, and driving responsible AI governance, security, resiliency, and adoption across a complex enterprise.

Leads Peregrine’s financial planning and analysis function, including long-range modeling, annual operating plans, forecasting, variance analysis, unit economics, investment cases, and executive reporting. The VP will build financial infrastructure for growth, support financing and IPO readiness, automate manual processes using AI, and recruit and develop a high-performing FP&A team. The role partners closely with the CFO, Controller, executive leadership, Board, and business leaders.

Partner with key business customers to optimize DigitalOcean cloud deployments, design architectures, troubleshoot technical challenges, drive retention and expansion, conduct business reviews, advocate for customer needs, and collaborate cross-functionally. The role also involves creating automation tools, delivering technical presentations and training, monitoring usage trends, and advising customers on cloud, AI/ML, cost, and performance optimization.

Lead the design, development, and operation of an enterprise GenAI serving platform. Build high-throughput LLM inference, gateway, routing, GPU optimization, quantization, distributed serving, and observability capabilities. Establish reliability practices, SLOs, performance benchmarks, cost controls, and secure production standards. Drive adoption of agentic AI-enabled engineering workflows with governance, auditability, and human validation while influencing senior stakeholders and enabling reusable platform components across teams.

Lead an agile engineering team to design, build, and operate secure, scalable Java/React cloud-native applications on AWS. Drive adoption of AI-assisted development practices, evaluate vendor solutions, provide technical guidance, and ensure production quality, stability, and secure responsible AI usage across the SDLC.

Lead and grow Tempus partnerships with biopharma clients by identifying prospects, conducting executive outreach, developing global account strategies, supporting contract negotiations, aligning cross-functional teams, and delivering revenue and strategic objectives. Travel ~20% and provide client feedback to inform product portfolio.

Support traded-products counterparty credit risk analysis by monitoring exposures, sizing limits, and improving exposure methodologies and tooling. Partner with sales, trading, credit officers, quantitative research, technology, and operations to perform deep dives, report risks, form risk appetite views, and drive AI-enabled workflow improvements and firmwide initiatives.

Legal Counsel will support US expansion by negotiating complex B2B SaaS agreements, advising AI and engineering teams on product risks, managing privacy and security compliance across jurisdictions, and developing scalable legal policies and processes. The role partners with executive leadership and addresses novel generative AI legal issues in a fast-growing technology startup.

Supports AI model development and testing for sourcing tools, including data preparation, analysis, forecasting, benchmarking, and classification. Collaborates with cross-functional teams on AI-led projects, researches emerging trends in AI and automation, tracks action items, and explores how technology can improve sourcing decisions related to cost, quality, sustainability, and product performance.

Lead global HR Operations process excellence by diagnosing workflows, analyzing performance data, standardizing processes, managing improvement initiatives, and identifying automation and AI opportunities. Partner with HR leaders, platform teams, product owners, and regional stakeholders to implement operating model changes, improve service delivery, maintain process standards, and foster consistent ways of working across the organization.

Leads software engineering and quality engineering for JPMorganChase’s Payments team. Builds and maintains large-scale test automation frameworks, integrates automated testing into CI/CD pipelines, and supports application development, system design, and operational stability. Drives responsible use of AI-assisted engineering tools, improves test quality and delivery speed, and establishes validation, security, and resiliency standards. Oversees complex, high-risk projects and promotes practices such as failure triage, contract testing, service validation, and canary testing.

Lead HR systems strategy and hands-on administration for Workday and ADP Workforce Now. Own integrations, security, data governance, reporting, vendor relations, and HRIS roadmap. Partner with Technology, Payroll, Finance, and People Operations. Provide functional leadership, training, and mentorship; hybrid role requiring local commuting in Eastern/Central time zones.

Leads the Claims insights and analytics function, partnering with senior Claims, Reserving, Actuarial, Finance, and Underwriting stakeholders. Translates business priorities into reporting, dashboards, data products, predictive analytics, AI, and automation initiatives. Oversees delivery, measurable business value, governance, stakeholder adoption, and team development while improving claims outcomes, operational efficiency, leakage management, reserving effectiveness, and decision-making.

Leads North American insights, analytics, and AI delivery supporting underwriting decisions, portfolio management, operational efficiency, and customer outcomes. Translates business priorities into measurable data products and analytics initiatives, oversees AI-enabled transformation, ensures responsible AI governance, and partners with underwriting and enterprise Data & Analytics teams. Develops high-performing teams, drives adoption, promotes agile and product-oriented delivery, and ensures scalable, reusable solutions that generate business value.

Lead technology risk and controls management for foundational platforms. Identify, quantify, report, and mitigate operational, compliance, and cybersecurity risks; evaluate control effectiveness; manage issues and governance; and advise technology stakeholders and senior leaders. Use authorized AI tools to synthesize evidence and develop reporting while validating outputs for security, auditability, data sensitivity, and regulatory compliance. Drive continuous control improvements and cross-functional collaboration.

Leads S&P Global’s enterprise digital assets and tokenization strategy, prioritizing and funding initiatives across divisions. Drives projects from exploration to production, builds external partnerships, develops commercial models, manages governance and regulatory alignment, and advises senior leadership. Leads a small team while influencing stakeholders across a global matrixed organization.

Leads an AI Evaluation Engineering team responsible for validating generative AI products, including intelligent agents and digital assistants. Provides technical direction, manages team performance and development, owns product quality, and establishes engineering best practices. The role requires expertise in GenAI architecture, evaluation methodologies, observability, automated testing, cloud and edge environments, reliability, safety, RAG assessment, and human-in-the-loop validation.