Top AI & Machine Learning Jobs

The role involves implementing ALM models in Python, collaborating with quant teams, analyzing performance, and contributing to software development in an Agile environment.

Lead hands-on designer for AI-enabled ITSM capabilities (Incident, Change, Problem, SACM, Business App, SLM). Translate workflows into scalable AI and automation solutions, prototype and validate designs, coach product teams, and partner with engineering, architecture, platform, and governance to deploy repeatable, risk-aware AI patterns.

Lead architecture and implementation of large-scale Intelligent Document Services. Design, code, test, and deploy AI-powered document classification, extraction, validation, and enrichment systems. Drive standards, mentor teams, collaborate with senior technical stakeholders, and help adopt generative AI and scalable microservices solutions across the enterprise.

Lead AI-enabled solution design for ITSM products (Incident, Change, Problem, SACM, etc.), prototype and validate models, coach product teams, and implement scalable, governed AI patterns across the ITSM portfolio.

Design, deploy, and operationalize enterprise AI/LLM applications (RAG, agents, vector DBs) to detect and mitigate emerging risks. Build prompt frameworks, dashboards, APIs, and governance controls; lead cross-functional initiatives and advise executives on AI-driven risk analytics.

Lead AI-enabled solution design for ITSM products (Incident, Change, Problem, SACM, etc.). Translate workflows into practical AI/automation designs, prototype and validate solutions, coach product and engineering teams, recommend fit-for-purpose patterns (deterministic, ML, generative, agentic, API), and partner with architecture, platform, and governance to scale repeatable AI patterns across the ITSM portfolio.

Design, deploy, and operationalize production AI/LLM and RAG solutions for enterprise risk analytics. Build agentic workflows, prompt libraries, APIs, and dashboards to detect emerging risks, support governance and compliance, and provide executive reporting. Lead cross-functional initiatives and mentor analysts to establish scalable AI-driven risk monitoring and data governance capabilities.

Lead architecture and development of large-scale Intelligent Document Services (IDOCS). Build and scale AI-driven document classification, extraction, validation, and enrichment solutions. Hands-on coding, design, and testing of microservices-based systems; mentor teams, define engineering standards, and drive adoption of generative AI and modern deployment practices.

Design, deploy, and operationalize production AI/LLM solutions (RAG, agents, vector DBs) to detect and monitor enterprise risks. Build prompt libraries, AI governance, APIs, dashboards and visualizations. Lead risk analytics, translate insights into executive reporting, advise stakeholders, and mentor analysts to scale AI-driven risk monitoring and remediation.

Lead end-to-end research and deployment of foundation models, LLMs, and agentic AI systems. Drive model development, rigorous evaluation, production transfer, collaboration with cross-functional teams, and publication of research while ensuring regulatory alignment and scalable engineering practices.