AIArchitect–EnterpriseStrategy

## Accountabilities Lead the design and hands-on development of enterprise-grade Generative AI and autonomous agent systems. Translate strategic business objectives into scalable AI architectures, workflows, and production-ready solutions. Facilitate executive-level workshops to define AI strategy, identify use cases, and assess data readiness. Build and deploy AI solutions using LLMs, vector databases, and orchestration frameworks across enterprise environments. Implement robust MLOps practices including monitoring, testing, governance, and bias mitigation. Integrate AI systems into enterprise platforms such as Salesforce, Workday, and cloud ecosystems (AWS, Azure, GCP). Continuously evaluate emerging AI tools, frameworks, and platforms to drive innovation and competitive advantage. Requirements: 6–10 years of experience in AI, machine learning, software engineering, or technical consulting roles. Strong hands-on experience building and deploying real-world Generative AI or agent-based systems. Deep understanding of autonomous agent architecture, including reasoning, planning, and tool use. Strong Python proficiency with experience using frameworks such as LangChain, LlamaIndex, AutoGen, or similar. Experience working with major cloud platforms (AWS, Azure, or GCP) and their AI/ML services. Proven ability to translate complex technical concepts into clear business value for executive stakeholders. Strong background in MLOps, model governance, and production-grade AI deployment practices. Excellent communication, consulting, and stakeholder management skills in enterprise environments. Benefits: Competitive compensation package aligned with senior AI architecture expertise. Performance-based incentives tied to project impact and innovation outcomes. Flexible remote or hybrid work arrangements depending on engagement structure. Comprehensive health, dental, and wellness benefits. Paid time off and supportive leave policies. Opportunity to design and deploy cutting-ed