Top AI & Machine Learning Jobs

Leads the design and implementation of AI-powered finance workflows, agents, copilots, and integrations across ERP, billing, procurement, and other financial systems. Establishes AI architecture, governance, security, observability, and responsible-use standards while partnering with Finance, IT, Security, Legal, and Audit. Identifies automation opportunities, measures business impact, builds reusable frameworks, and enables nontechnical teams to adopt AI solutions.

Leads the design and implementation of AI-powered Finance workflows, agents, copilots, and integrations across ERP, billing, procurement, and related systems. Establishes AI architecture, governance, security, testing, observability, and responsible-use practices. Partners with Finance, IT, Security, Legal, and Audit to identify automation opportunities, define success metrics, build reusable frameworks, and enable nontechnical teams. Requires technical leadership, enterprise financial systems integration, LLM experience, and the ability to build scalable 0-to-1 solutions.

Build and scale core ML platform infrastructure for model training, deployment, feature storage, real-time retrieval, inference, and monitoring. Lead architecture and technical execution, write production backend code, conduct design and code reviews, mentor engineers, improve reliability and cost efficiency, and partner with ML, product, data science, infrastructure, and security teams on platform strategy and roadmap.

Build scalable backend systems and AI-powered conversational products, including agent workflows, tool use, retrieval, orchestration, structured outputs, and asynchronous processing. Develop evaluation, reliability, observability, and production monitoring capabilities for AI systems. Collaborate with customers and cross-functional teams to improve products, participate in on-call support, and optimize quality, latency, cost, and performance.

Design and build scalable backend systems and production AI agent applications, including orchestration, retrieval, tool use, evaluation, guardrails, and distributed workflows. Improve reliability, observability, latency, cost, and quality while supporting high-volume workloads. Collaborate directly with customers and cross-functional teams to identify needs, diagnose incidents, and guide product improvements. Participate in on-call rotation and independently own ambiguous technical problems.

Lead architecture and scaling of Klaviyo’s high-throughput orchestration platform while integrating AI-driven agentic workflows and automated decision-making. Establish foundational services, AI-native development practices, evaluation frameworks, and high engineering standards. Partner with product, data science, design, customers, and executives to shape platform strategy. The role requires deep backend, distributed systems, cloud infrastructure, Python, and production AI experience, with responsibility for mentorship and technical leadership.

Lead the technical and product direction for a production conversational AI customer agent. Build and scale agentic systems covering orchestration, evaluation, guardrails, memory, context, reliability, and failure handling. Remain hands-on with coding, architecture, debugging, and production operations while mentoring engineers and partnering with product, design, data science, and go-to-market teams. The role is based in-office in Boston and may require up to 10% travel.

Lead the technical and product direction for a production conversational AI customer agent. Build and scale agentic systems involving orchestration, evaluation, guardrails, memory, context, reliability, and failure handling. Write and review code, make architecture decisions, collaborate cross-functionally, mentor engineers, evaluate emerging AI technologies, and support systems through launch and live customer usage.

Build and maintain backend services and large-scale data pipelines for recommendation systems, productionize ML models (batch and real-time), develop vector database capabilities, ensure observability and reliability, lead A/B testing and data-driven decisions, participate in on-call and incident response, and mentor engineers while integrating AI into development workflows.

Own the architecture and development of Klaviyo’s enterprise MarTech ecosystem, connecting marketing data, customer journeys, campaign execution, budgeting, and performance insights. Build AI-powered capabilities including generative AI, predictive scoring, and intent automation. Architect integrations across HubSpot, Salesforce, NetSuite, Coupa, and internal systems, advise on technical designs, support vendor evaluations, and partner cross-functionally to improve marketing efficiency and ROI.