Design and implement AI applications on Snowflake using Cortex AI functions, agents, and search capabilities. Collaborate with clients and engineering teams to build secure, scalable data foundations and AI-driven systems.
You will work directly with clients, engineers, and AI specialists to implement AI solutions. Your role involves translating emerging technologies into measurable business outcomes for financial institutions.
Lead, coach, and grow a team of forward deployed engineers while owning delivery quality, scope, timelines, and outcomes across concurrent client engagements. Work hands-on to build and review AI systems, lead client technical sessions, identify follow-on opportunities, and establish reusable delivery practices.
You will architect and build foundational data pipeline infrastructure to support a decentralized Data Mesh strategy and AI-ready semantic layers. Additionally, you will lead a small data engineering team and mentor analysts to enable self-service data product development.
You will design and maintain robust data models, pipelines, and semantic layers to ensure data is structured and ready for AI agents. Additionally, you will act as a bridge between technical data infrastructure and business stakeholders to drive measurable outcomes.
Lead architecture for lakehouse implementations and platform modernization while serving as the primary technical voice for the Databricks partnership. Support the sales pipeline by conducting discovery calls, architecture workshops, and shaping technical solutions for clients.
Design and develop end-to-end cloud data pipelines while optimizing ETL processes for scalability and performance. Lead a team of data engineers by providing technical guidance and collaborating with stakeholders to deliver actionable insights.
Design, build, and deploy advanced AI solutions using LLMs, RAG, and agentic architectures to automate workflows and transform unstructured data. Collaborate with cross-functional teams to deliver high-impact, production-ready AI applications across cloud platforms.
Design and maintain analytical data structures and scalable ETL/ELT pipelines to produce reliable business metrics, detect unusual customer spending behavior, and automate business-rule-based triggers. Work with technical and business stakeholders and Data Science colleagues to validate requirements, build analytical features, ensure data quality, and document and evolve solutions through agile sprints.
Lead technical pre-sales and discovery sessions to demonstrate Claude Code and Claude Cowork capabilities to prospective clients. Design and deliver advanced technical enablement workshops for engineering teams while managing architectural and security-related inquiries.
Lead AI enablement programs by facilitating workshops, training sessions, and developing strategies to drive organizational adoption. Partner with technical teams and business stakeholders to translate AI capabilities into measurable business outcomes while navigating governance and compliance requirements.
Lead the end-to-end architecture and delivery of enterprise-grade Power Platform and Copilot Studio solutions for clients. Define governance frameworks, security standards, and integration patterns while facilitating discovery workshops and stakeholder communication.
Build and scale robust data solutions and high-performance pipelines for extraction, loading, and transformation. Collaborate with stakeholders to transform business use cases into production-ready services while ensuring data quality through rigorous testing.
Design and implement cloud-based data architecture solutions to optimize storage, retrieval, and processing for clients. Collaborate with cross-functional teams to translate business requirements into effective data strategies and mentor junior team members.
Design and implement scalable AI-driven applications on the Azure platform using a full-stack approach. Collaborate with cross-functional teams to integrate AI frameworks and optimize cloud-native deployments for performance and cost.
