AI Engineer Lead

Job Summary Cl ient. is seeking a highly experienced Senior AI Engineering Lead (Contractor) to join the Generative AI team supporting Brand Growth Systems (BGS). This hands-on technical leadership role will drive the design, development, and deployment of an AI orchestration layer that powers automated insight generation across the organization. The successful candidate will collaborate closely with Business stakeholders, the Generative AI Center of Excellence (COE), Data Science, Machine Learning, and Platform teams to build scalable, production-grade AI solutions. This role is central to advancing the organization's AI maturity from proactive insight generation to agentic and autonomous AI systems while establishing engineering standards, governance, and best practices for enterprise AI adoption. Key Responsibilities AI Architecture & Solution Design Lthe design, development, and deployment of an enterprise AI orchestration layer for Brand Growth Systems. Define architecture patterns, technical standards, and engineering best practices for scalable AI solutions. Design robust and secure AI systems capable of supporting enterprise-level business operations. Evaluate emerging AI technologies, frameworks, and methodologies to support business growth objectives. AI Orchestration & Integration Bu ild and enhance orchestration capabilities across three primary intelligence sources: Snowflake Semantic Views utilizing Cortex Analyst for natural language access to governed data. Machine Learning Models developed by Data Science and ML teams. Unstructured Content including playbooks, guidelines, documentation, and knowledge repositories. Integrate Large Language Models (LLMs), AI agents, machine learning models, APIs, and data pipelines into unified AI-powered services. Develop and deploy production-ready AI workflows on Azure cloud platforms. Agentic & Autonomous AI Development Ar chitect and implement agentic AI workflows that support the evolution from proactive to autonomous insight generation. Design intelligent systems capable of reasoning, planning, decision-making, and task orchestration. Drive rapid prototyping, experimentation, and iterative product development while ensuring enterprise-grade quality and scalability. AI Governance, Monitoring & Responsible A I Establish AI engineering standards covering: E valuation methodologies Observability and monitoring Security controls AI governance Responsible AI practices Implement AI guardrails, including: Output validation Grounding mechanisms Hallucination mitigation Content filtering Response quality controls Ensure compliance with organizational security and privacy requirements. Cross-Functional Collaboration Partner with Business stakeholders, the Gen AI COE, Data Science, Machine Learning, and Platform teams to translate business objectives into technical solutions. Collaborate with Snowflake platform teams and enterprise technology partners to support system integration and optimization. Facilitate technical decision-making and communicate architecture designs, trade-offs, and strategic recommendations to technical and non-technical audience s. Leadership & Mentorship Pr ovide technical leadership and mentorship to engineering teams and cross-functional partners. Establish development best practices and AI implementation standards. Support knowledge sharing and capability-building initiatives across the organization. Promote innovation and continuous improvement within the AI engineering function. Required Qualifications Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, or a related field. Minimum 8+ years of experience in Software Engineering, AI Engineering, Machine Learning Engineering, or related disciplines. Minimum 2+ years of technical leadership experience leading engineering teams or enterprise AI initiatives. Proven experience designing, developing, and deploying AI/ML and Generative AI solutions in production environments. Experience with AI orchestration and agentic frameworks such as: L angChain LangGraph Semantic Kernel AutoGen Similar orchestration technologies Strong hands-on experience with Microsoft Azure technologies, including: Azure OpenAI Azure Machine Learning Azure Functions Azure Kubernetes Service (AKS) Azure Data Services Experience with Snowflake, including: Semantic Views Cortex Analyst Similar semantic-layer or text-to-SQL techn ologies Strong understanding of: Ma chine Learning concepts MLOps and LLMOps practices Model lifecycle management Model deployment and monitoring Experience building Retrieval-Augmented Generation (RAG) and document intelligence solutions. Strong programming experience with Python. Experience developing APIs, microservices, and distributed systems. Experience working in large enterprise, cross-functional environments. Strong analytical, problem-solving, and communication skills. Demonstrated ability to operate independently with a high degree of ownership and accountability. Preferred Qualifications Experience with: V ector databases Prompt engineering frameworks Agent evaluation frameworks RAG optimization techniques Experience in Consumer Packaged Goods (CPG), Retail, Consumer Insights, Marketing Analytics, or Brand Analytics domains. Knowledge of enterprise AI governance, security, compliance, and Responsible AI frameworks. Experience scaling AI capabilities through Centers of Excellence (COEs) or enterprise AI platform teams. Experience supporting globally distributed and matrixed organizations. Experience with advanced AI monitoring, observability, and model evaluation platf orms. Certifications (If Any) Microsoft Certified: Azure AI Engineer Associate (Preferred) Microsoft Certified: Azure Solutions Architect Expert (Preferred) Microsoft Certified: Azure Data Scientist Associate (Preferred) Snowflake Certification(s) (Preferred) Relevant AI/ML, Cloud, Data Engineering, or MLOps certifications are a plus. Top Qualifications 8+ years of AI, ML, or Software Engineering experience with technical leadership responsibilities. Deep expertise in Azure AI services, Generative AI, AI orchestration frameworks, and enterprise-scale solution architecture. Strong experience with Snowflake, RAG pipelines, agentic AI systems, and implementation of AI governance and guardrails in production environments. Education: Bachelors Degree Certification: Microsoft Certified: Azure AI Engineer Associate , Microsoft Certified: Azure Solutions Architect Expert