Senior Enterprise AI Engineer, IT Operations

Our Mission: 6sense's mission is to multiply what matters: growth, retention, and efficiency.  We envision a future where companies, teams and people reach their full potential. Our People: People are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging.  Every 6sensor plays a part in defining the future of our industry-leading technology.  6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers.  We want 6sense to be the best chapter of your career.  Senior Enterprise AI Engineer, IT Operations About the Role We're looking for a Senior Enterprise AI Engineer to help scale internal operations through AI-driven systems, workflow automation, and intelligent agents. This role will build and deploy secure, production-ready AI solutions that improve employee productivity, automate business processes, and enhance decision-making across the organization. Success in this role is measured by delivering impactful AI-powered solutions that solve real business problems while maintaining security, reliability, and compliance. Key Responsibilities 1. AI Systems and Agent Development Design, build, and deploy enterprise AI solutions using Workato, MCP frameworks, Microsoft 365 Copilot, Claude, and related technologies. Develop AI agents and assistants that automate workflows across IT, Security, Finance, HR, Legal, and GTM functions. Contribute to reusable patterns for agent orchestration, prompt design, context management, and human review workflows. 2. Enterprise Automation and Integration Build and maintain end-to-end automated workflows using Workato and related integration platforms. Integrate SaaS applications, internal systems, and data services into AI-powered business workflows. Identify opportunities to reduce manual effort through automation and process optimization. 3. AI Governance, Security, and Risk Implement security, privacy, and compliance requirements within AI solutions. Follow established governance frameworks and best practices for responsible AI. Apply controls that protect against data leakage, prompt injection, and unauthorized access. Partner with Security and IT teams to ensure AI systems operate safely and compliantly. 4. Platform Enablement and Scale Develop reusable AI components, templates, and integrations that accelerate adoption across teams. Document best practices and implementation patterns. Support internal teams in deploying and expanding AI-enabled workflows. 5. Productivity and Employee Experience Leverage Microsoft 365 Copilot, Claude, and related tools to improve employee productivity. Identify and implement high-value AI use cases across business functions. Measure and optimize the effectiveness of deployed AI solutions. 6. Cross-Functional Collaboration Partner with business stakeholders to understand operational challenges and define solutions. Translate requirements into scalable technical implementations. Collaborate with IT, Security, Enterprise Applications, and business teams to deliver successful outcomes. Required Qualifications 5+ years of experience in enterprise engineering, software engineering, automation, or IT systems. Hands-on experience building integrations and workflows using Workato, Tines, or similar platforms. Experience working with LLM-based applications, prompt engineering, AI assistants, or agent frameworks. Strong understanding of APIs, integrations, and SaaS ecosystems. Experience implementing security and compliance controls within cloud-based environments. Strong problem-solving skills and ability to independently deliver technical solutions. Preferred Qualifications Experience with MCP or similar agent and context management frameworks. Experience extending Microsoft 365 Copilot and leveraging Microsoft Graph APIs. Experience with Claude or other enterprise AI platforms. Familiarity with AI governance and responsible AI principles. Experience supporting internal platforms or business systems within a SaaS company. Core Competencies AI and automation mindset. Strong software and systems engineering fundamentals. Security-conscious development practices. Cross-functional collaboration and communication. Ability to simplify business processes through technology. Bias for execution and continuous improvement. Success Metrics Deployment of production-ready AI solutions that improve business operations. Reduction in manual effort and operational overhead. Increased productivity through automation and AI adoption. Reliability, security, and compliance of deployed solutions. Successful delivery of AI initiatives within scope and timeline. What Good Looks Like Delivers production-ready AI solution