Currently operating as a high-performing analytics team, we are on an exciting journey to transform our operations by embedding AI into every layer of our processes and decision-making frameworks. Our team is focused on evolving from traditional analytics to leveraging cutting-edge AI technologies, enabling smarter workflows, predictive insights, and automation at scale.
As part of this transformation, we are integrating advanced machine learning models, large language models (LLMs), and AI-driven solutions into our operations to enhance efficiency, drive innovation, and unlock new opportunities for growth. Joining us means being part of a forward-thinking team that is redefining how analytics and AI can work together to create impactful solutions for the organization and its stakeholders.
Who you are:The AI Lead will architect unified systems that merge generative AI capabilities with traditional BI workflows. This involves designing Snowflake-native pipelines that feed both machine learning models and Tableau dashboards, enabling real-time analytics augmented by predictive insights. A critical responsibility includes implementing text-to-SQL interfaces to allow natural language querying of enterprise data warehouses, reducing dependency on technical teams for routine reporting.
The position requires reimagining ETL processes through AI automation, replacing manual data preparation with ML-powered anomaly detection and schema optimization algorithms. Successful candidates will demonstrate experience deploying multi-agent AI systems that generate dashboards, monitor KPIs, and trigger alerts through integrated BI platforms
Responsibilities:Build and deploy AI applications across domains such as deep learning, NLP, LLMs (e.g., GPT-4, Claude) and RAG (Retrieval-Augmented Generation).Demonstrate strong proficiency in machine learning frameworks and programming languages (Python).Architect, plan, and implement AI systems for clients by developing robust data pipelines, ML pipelines, and strategies for training and serving models efficiently.Design end-to-end ML operations, including data flow architecture and deployment pipelines, while ensuring scalability and reliability of AI solutions.Develop and deliver Tableau dashboards that exemplify excellence in design, functionality, and performance, ensuring they are visually compelling, data-driven, and tailored to meet complex business requirements effectively.Develop and optimize prompts for advanced LLMs (e.g., GPT-4, Claude 3.5 Sonnet) and design prompt strategies for AI agent frameworks like LangChain and Hugging Face.Drive the replacement of manual workflows with AI-driven automation to enhance operational efficiency across business processes.Lead technical deep dives, proofs of concept, workshops, and internal sprints to design industry-specific AI solutions that align with customer needs and promote adoption success.Work closely with internal AI business units, engineering teams, and product managers to provide market feedback on products and solutions while ensuring successful deployment of AI initiatives.Stay updated on emerging trends in AI/ML technologies to guide the development of cutting-edge solutions that address industry challenges effectively.Mentor junior engineers, foster a culture of innovation within teams, and promote continuous learning in AI/ML practices.Basic Qualifications:Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, or a related technical discipline.10+ years of professional BI &Analytics experience, including 3+ years in AI/machine learning roles.Proven expertise in Large Language Models (e.g., OpenAI, Anthropic, Google, Llama) and Agentic AI frameworks.Minimum 6+ years of hands-on experience in Python programming.Advanced proficiency in SQL with hands-on experience optimizing queries in Snowflake for large-scale datasets.Strong knowledge of Tableau for creating interactive dashboards integrated with AI-driven insights.Strong proficiency in machine learning frameworks (TensorFlow, PyTorch) applied to complex problem-solving scenarios.Expertise in developing large-scale AI applications leveraging advanced techniques like RAG (Retrieval-Augmented Generation) and Agent-based architectures.Deep understanding of ML modeling, deep learning architectures, transformer models, and GenAI frameworks (LangChain, LangGraph, LangSmith etc.)Hands-on experience in building, deploying, and scaling GenAI agents in production environments.In-depth understanding of LLM/MLOps, including model evaluation, experimentation, and lifecycle management.Demonstrated leadership abilities in strategic decision-making, cross-functional collaboration, and driving AI innovation.Exceptional problem-solving, communication, and stakeholder management skills.Preferred Qualifications:Experience deploying multi-agent systems for automating complex BI tasks like report generation or trend analysis.Hands-on experience with Snowflake Cortex or similar tools for enabling natural language queries against data warehouses.Familiarity with MLOps tools (e.g., Kubeflow) for managing the lifecycle of machine learning models.Demonstrated success in integrating advanced AI solutions into enterprise BI platforms to drive measurable business outcomes.#WeAreCisco (This is the Standard and cannot be changed)
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