Top AI & Machine Learning Jobs

Design, prototype, and deploy LLM-powered agents, RAG workflows, and automations that accelerate internal teams and customer-facing product features. Integrate AI systems with SaaS tools, build reusable components and evaluation frameworks, embed with business teams to deliver measurable outcomes, and establish standards for responsible AI, monitoring, and cost control across the company.

The Senior AI Product Engineer will develop and optimize AI product features, ensuring a seamless user experience through collaboration with engineering teams. Responsibilities include building full-stack features, implementing user feedback mechanisms, and monitoring product performance.

Lead product strategy and roadmap for AI and data products for SMEs; manage cross-functional global teams; ensure security/compliance; drive go-to-market, pricing, customer engagement, and on-time, on-budget delivery.

The Senior AI Engineer will design and build AI-powered automation tools, maintain LLM systems, and collaborate with business analysts to enhance processes across various operations.

Lead strategy and delivery of AI-powered, agentic product features for a SaaS insurance platform. Define roadmaps, KPIs, ROI, and success criteria; collaborate with engineering and data science to prototype, test, and launch; drive adoption, mentor junior PMs, and align cross-functional teams from discovery through GTM.

Design, build, and own production AI agents and automations for marketing. Integrate and instrument the marketing stack (Salesforce, HubSpot, Qualified, Clay, ZoomInfo, data warehouse), implement predictive scoring and personalization, monitor systems for reliability, and collaborate with marketing, RevOps, and sales to translate problems into deployable software.

Use AI coding agents to build end-to-end applications, automations, and basic agents. Translate customer needs into deployed solutions, instrument and iterate on outcomes, evaluate AI output for security/privacy/quality, engage with customers, and document prompts and patterns.

Lead design and implementation of LLM-powered conversational financial interfaces. Architect secure, zero-trust orchestration (tools, chains, policy layers), own full-stack services and data pipelines, partner with product, and mentor global teams to deliver production-grade intelligent customer experiences.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

Lead and grow a distributed engineering team to build and scale AI platforms and agents for healthcare. Own technical strategy, data/retrieval/semantic architectures, ML model serving and MLOps, and deliver HIPAA-compliant, cloud-native systems in partnership with Product, Data Science, and Clinical teams.