AIArchitect–EnterpriseStrategy

## Accountabilities Lead the design and implementation of enterprise-grade generative AI and autonomous agent architectures tailored to complex business use cases. Translate strategic client objectives into scalable AI solutions, including workflow orchestration, multi-agent systems, and LLM-based applications. Act as a trusted advisor to senior stakeholders, facilitating workshops to identify high-value AI opportunities and define adoption roadmaps. Build and deploy production-ready AI systems using modern frameworks, APIs, vector databases, and cloud AI services. Define and enforce best practices for responsible AI, including observability, testing, governance, and mitigation of bias and hallucinations. Integrate AI solutions into enterprise ecosystems such as CRM, ERP, and cloud platforms to enable seamless business adoption. Evaluate and experiment with emerging AI tools, frameworks, and platforms to continuously enhance solution capabilities. Collaborate with cross-functional teams to ensure successful delivery, scaling, and operationalization of AI initiatives. Requirements: 6–10 years of experience in software engineering, AI/ML engineering, or technical consulting roles. Strong hands-on experience building and deploying generative AI or machine learning solutions in production environments. Deep understanding of LLMs, agent-based architectures, reasoning systems, and tool-use frameworks. Strong Python programming skills with experience using frameworks such as LangChain, LlamaIndex, AutoGen, or similar. Experience working with cloud AI services (AWS, Azure, or GCP) and enterprise integration environments. Ability to translate business problems into technical AI architectures and communicate effectively with executive stakeholders. Experience with vector databases, prompt engineering, and orchestration of multi-step AI workflows. Strong knowledge of MLOps principles, including monitoring, evaluation, and deployment of AI systems. Excellent problem-solving, co