Top AI & Machine Learning Jobs

Lead end-to-end product development for AI features in an observability platform. Engage customers to define problems, set strategy and roadmap, collaborate with engineering/design/applied AI, and ship AI capabilities (agents, workflows, intelligent experiences). Measure adoption, usage, and business impact while handling discovery, delivery, and adoption.

Design, build, and deploy AI-driven observability solutions. Develop LLM/NLP and generative AI features (RAG, semantic search, embeddings) for incident reports, root-cause analysis, and remediation guidance. Optimize models for real-time, cloud-native deployment (AWS/GCP, Kubernetes), and collaborate with product, platform, and engineering teams to integrate AI capabilities across the LogicMonitor platform.

Customer-facing engineering role building and deploying AI-powered observability solutions. Ship backend and full-stack integrations, instrument telemetry, configure cloud/kubernetes deployments, and convert field learnings into reusable artifacts and product feedback.

Designs and scales AI-powered go-to-market workflows across marketing, sales, customer success, and revenue operations. Responsibilities include building AI copilots and agents, automating lead-to-renewal processes, integrating Salesforce and other GTM tools, operationalizing LLMs, improving CRM data quality, enabling predictive analytics, and delivering recommendations that improve pipeline conversion, forecasting, seller productivity, retention, and expansion.

Customer-facing engineering role building and deploying AI-powered observability solutions. Design, implement, and support integrations, backend services, telemetry pipelines, and full-stack artifacts using Python, Java, and JavaScript/TypeScript. Drive production rollouts, troubleshooting, and codify repeatable templates and playbooks to improve adoption and product feedback.

Design and build production-grade evaluation systems for Edwin AI, including golden datasets, automated graders, regression suites, and offline and online pipelines. Evaluate LLM agents, retrieval, tool use, reasoning, safety, and operational workflows. Monitor quality and behavioral drift, analyze failures, translate expert judgment into evaluation frameworks, and establish evaluation-driven development practices while mentoring engineers.

Own success for a portfolio of strategic enterprise customers by driving AI adoption, developing AI Success Plans, measuring ROI, managing customer health, engaging executives, identifying expansion use cases, leading cross-functional recovery plans, mentoring peers, and providing product feedback to improve value realization and Autonomous IT maturity.

Own customer success for strategic enterprise accounts, guiding deployment to operational adoption, value realization, and Autonomous IT maturity. Develop and execute AI Success Plans, deliver executive reviews, identify and remediate adoption risks, lead cross-functional initiatives, drive expansion, represent customer feedback to product and GTM, and mentor other AI Growth Strategists.