Top AI & Machine Learning Jobs

Partner with business leaders to define AI strategy, set KPIs, and deliver executive reporting; prototype AI solutions (e.g., Google AI Studio); remove operational obstacles across ServiceNow, Jira, and automated workflows; enforce data governance and privacy to enable enterprise AI adoption and measurable ROI.

Design, build, and deploy enterprise-grade autonomous AI services and multi-agent systems. Implement MCP and A2A integrations, architect hybrid control flows and state machines, integrate sandboxed tool execution with strict egress controls, and apply SRE principles for observability, fallback mechanisms, and reliability to move generative AI from POC to production.

Lead scaling of AI initiatives across Direct Sales by translating call and performance data into prioritized AI roadmaps, driving deployment, managing cross-functional stakeholders, mitigating risks, and reporting ROI-focused insights to senior leadership.

Lead and grow a team of Agentic AI engineers to transition multi-agent and generative AI POCs into scalable, secure, production-ready services. Define technical roadmap, guide architecture for scalability and cost, champion agent interoperability standards, and establish CI/CD, observability, and delivery practices for LLM-powered applications that drive business impact.

Lead the global transition from traditional SDLC to AI-enhanced development by executing the enterprise roadmap, embedding AI governance and security into SDLC gates, establishing KPI dashboards, scaling training and AI Champions, and managing people and culture risks to drive measurable AI adoption and ROI.

Lead and mentor an AI engineering team to design, architect, and deploy production-ready multi-agent, LLM-powered systems. Define technical strategy, set architecture and security standards, implement hybrid control flows/state machines, integrate agent-to-tool and agent-to-agent protocols, and collaborate with product and business teams to translate requirements into scalable microservices.

Lead AI product strategy for enterprise shared services, prioritize and govern AI requests, and drive deployment of generative AI/LLM and ML solutions. Manage cross-functional teams to convert manual processes into automated workflows, build reusable AI components and datasets, and deliver measurable operational efficiency and cost reductions across internal systems.

Partner with HR leaders to define AI strategies, build KPIs, and deliver ROI. Design and deploy generative AI prototypes (e.g., Google AI Studio), integrate across ServiceNow, Jira, and HRIS, enforce data governance and compliance, automate executive reporting and workforce analytics, and translate technical solutions for non-technical HR stakeholders to accelerate AI adoption.

Embed AI solutions across legal and corporate affairs to remove workflow bottlenecks, build rapid prototypes for contract analysis and regulatory tracking, enforce data governance, and deliver executive reporting and KPIs to drive legal operations efficiency and risk mitigation.