Top Artificial Intelligence Jobs

Build and support AI-powered workflows and automation for Gusto’s go-to-market teams. The role contributes to GTM AI strategy, evaluates models and vendors, integrates Salesforce and other GTM systems with data warehouses, and develops evaluation frameworks measuring reliability, latency, cost, and business impact. It also coordinates cross-functional implementation, training, adoption, and reusable guardrails across Sales, Marketing, and Partner teams.

Leads development of secure, scalable data and AI platform solutions, including batch and real-time pipelines, ETL/ELT workflows, data modeling, governance, cataloging, lineage, quality frameworks, and semantic layers. Builds Agentic Autonomous Lakehouse capabilities for governed self-service provisioning and operational optimization. Partners with technical and business stakeholders, reviews production code, improves system stability, evaluates architectures and vendors, and promotes emerging technologies across engineering communities.

Lead software engineering for JPMorganChase’s Digital Utilities team by designing, developing, testing, debugging, and operating secure, scalable Java microservices on AWS. Review production code, improve application resiliency, automate recurring remediation, and promote CI/CD and secure development practices. Drive responsible adoption of AI-assisted engineering tools for coding, reviews, testing, troubleshooting, and root-cause analysis. Evaluate vendor and startup technologies, assess architectural designs, and coach engineers on compliant AI usage.

Leads software engineering within an agile Digital Utilities team, designing, developing, testing, debugging, and maintaining secure, scalable Java and cloud-native applications. Reviews code, improves operational stability, automates recurring remediation, and promotes enterprise-approved AI-assisted engineering practices with secure validation standards. Evaluates vendor and internal architectural solutions, coaches engineers on responsible AI adoption, and applies software development lifecycle, resiliency, security, and financial-services technology expertise.

Leads business systems analysis and end-to-end solution design for AI-powered Enterprise KYC modernization. Defines requirements, agentic workflows, decision frameworks, data strategies, evaluation metrics, governance controls, and process improvements. Partners with business, operations, data, engineering, risk, legal, and compliance teams to deliver scalable, auditable GenAI and agent-based solutions. Supports pilots and production implementations while measuring business value, model effectiveness, reliability, compliance, and user adoption.

Leads Capital One’s enterprise AI learning and enablement strategy, developing workforce-readiness roadmaps, technology adoption programs, and scalable change initiatives. Partners with technology, strategy, and HR leaders to increase AI fluency, operational tool adoption, and measurable behavior change. Translates advanced AI concepts into practical enablement tools, manages complex cross-functional programs, influences executives, oversees vendors, and uses analytics to prioritize learning investments and demonstrate ROI.

Leads and mentors a backend engineering team building cloud-native provisioning and orchestration services for CrowdStrike’s AI Detection and Response platform. Owns technical vision, architecture, roadmap, reliability, incident response, engineering practices, hiring, and team development. This player-coach role includes approximately 20–30% hands-on coding, collaboration with product and engineering stakeholders, and delivery of scalable distributed systems supporting large-scale security event processing.

As a Software Engineer Lead, you will design and develop AI solutions, lead tech teams, and ensure high-quality NLP capabilities. You'll integrate AI services into enterprise platforms and guide best coding practices.

Build and scale AI-ready data platforms for biotherapeutics research. Develop data products, machine learning and agentic AI pipelines, integrate public and proprietary datasets, and improve data governance, metadata, storage, visualization, and analysis. Collaborate with scientists, external companies, and academic institutions while supporting platform adoption through training and workshops. Publish and present scientific work and take solutions from prototype to production.

Leads Pfizer’s US Commercial AI portfolio governance, value realization, and operating model. Establishes federated build standards, intake processes, shared registries, controls, prioritization frameworks, and responsible AI requirements. Partners with executive stakeholders across technology, data, legal, privacy, compliance, and security to assess platforms, manage dependencies, guide investment decisions, and scale agentic AI. Builds and leads a cross-functional team while embedding AI-first practices across Commercial and the Chief Marketing Office.

Leads Dynatrace’s enterprise AI strategy, roadmap, governance, and value realization across global business functions. Evaluates AI technologies, vendors, platforms, and build-buy-partner decisions; establishes responsible AI policies and risk controls; and builds AI enablement programs and a Center of Excellence. Advises executives, measures productivity and ROI, drives organizational adoption, and guides enterprise AI architecture and deployment reliability.

Leads and develops a team building AI enablement tools, developer tooling, reusable accelerators, automation, and shared engineering systems. Remains hands-on with coding, code review, prototyping, and AI-assisted development. Drives production adoption of AI through evaluation, governance, observability, resilience, and operational best practices. Establishes ownership in ambiguous environments and influences architecture, strategy, and infrastructure investment across engineering, security, product, and leadership teams.

Leads and mentors an engineering team building AI enablement platforms, developer tooling, automation, reusable accelerators, and shared engineering systems. The role remains hands-on with coding, code review, prototyping, architecture, production AI adoption, evaluation, governance, observability, resilience, and operational improvement. It partners across engineering, security, product, and leadership to define ownership, strategy, infrastructure investment, and measurable adoption outcomes.

Design, develop, deploy, and scale enterprise AI products, agents, automations, and intelligent workflows for the People Organization. Build multi-agent systems integrating Workday, ServiceNow, Microsoft Copilot, and other enterprise platforms through APIs and event-driven architectures. Apply HR domain expertise to employee lifecycle processes, ensure secure and responsible AI governance, and implement monitoring, testing, observability, and evaluation frameworks. Partner with business and technology leaders to prototype AI solutions and drive adoption and measurable workforce transformation.

Leads architecture and development of scalable, AI-powered travel experiences. Responsibilities include high-level system design, cross-service integration, AI/ML adoption, agentic AI development, feedback and evaluation pipelines, operational excellence, incident response, technical vision, and mentoring engineers. The role requires driving reliable production systems, model governance, safety, observability, and continuous improvement across teams and domains.

Design, build, and maintain customer-facing digital commerce services (checkout, billing, subscriptions, catalog, cart, orders). Use AI-assisted workflows for coding, testing, review, and documentation. Develop scalable, low-latency APIs and services, improve observability, automation, and engineering practices, and partner with cross-functional teams to deliver reliable solutions.

Lead technical customer engagements to design, integrate, and launch AI-driven solutions on the Moveworks Platform. Build secure integrations (APIs, iPaaS, serverless), advise on agentic AI roadmaps, drive adoption across enterprise customers, and feed product/engineering with field feedback. Travel to customer sites up to 25% and generalize solutions into reusable templates.

Lead Microsoft Dynamics 365 CRM implementations, architect solutions, manage project lifecycles and client accounts, mentor teams, ensure quality and post-go-live support, and drive innovation and continuous improvement.

Lead design and delivery of AI-driven P&C insurance operations solutions: analyze client needs, architect and implement AI/software solutions, manage projects and budgets, coach teams, train clients, ensure adoption, and maintain standards, governance, and evaluation practices to drive operational efficiency and innovation.

Lead design and evolution of customer-facing digital commerce systems (checkout, billing, payments, subscriptions, catalog, cart, orders). Use AI-assisted workflows to accelerate coding, review, testing, and documentation while ensuring security and production readiness. Drive architecture and API decisions across modern web apps, improve engineering excellence (testing, automation, observability, DevOps), build reusable patterns, and coach engineers to raise team productivity and technical delivery.

Leads and mentors an SDET team while remaining hands-on with test frameworks, automation, tooling, debugging, and code reviews. Owns functional, performance, contract, and chaos testing strategy for large-scale distributed AI security services. Establishes CI/CD quality gates, improves observability and resilience, partners with engineering and product teams, manages planning and delivery, and recruits and develops engineering talent. The role also uses AI-powered tools to improve testing efficiency.

Designs, develops, tests, deploys, documents, maintains, and debugs scalable production software. Serves as technical owner for complex services, collaborates with product and platform teams, translates business requirements into technical solutions, and mentors engineers while balancing quality, performance, and risk.

Lead the development of AI-driven test automation frameworks for cloud-native systems, focusing on quality engineering and mentoring.

Lead enterprise strategy and architecture to make data AI- and agent-ready. Define standards for metadata, semantic layers, governance, RAG/vector retrieval, agent orchestration, APIs, and DevSecOps to embed Agentic AI across data engineering and platforms while influencing stakeholders and driving adoption.

Build secure, scalable platforms and automation for cybersecurity operations, including threat hunting, incident response, PSIRT, product security, vulnerability management, and analyst workflows. Develop LLM-powered agents, integrate SIEM, SOAR, cloud, endpoint, ticketing, and scanning systems, and process high-volume security telemetry. Partner with security teams to automate investigations, enrich alerts, prioritize risks, track remediation, and deliver reliable production services.