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Designs, builds, and maintains scalable AWS data pipelines, integrations, lakehouse infrastructure, and Airflow workflows. Processes commercial pharmaceutical data, supports pharma KPIs and analytics, and develops pipelines for AI, machine learning, generative AI, LLM, embeddings, and RAG applications. The role also includes legacy-system migration, pipeline monitoring and optimization, data quality assurance, and translating pharmaceutical business needs into reliable data solutions.

Lead design and delivery of Snowflake-centric cloud data platforms. Engage with clients to gather requirements, architect scalable secure solutions, provide technical leadership, develop roadmaps, advise executives, and guide implementation best practices across the analytics stack.

Lead the design, development, and optimization of scalable batch and real-time data pipelines and platforms. Build cloud-based data solutions using distributed processing, streaming technologies, and modern data warehouses. Define data models, improve performance and reliability, establish engineering best practices, and provide technical guidance to data engineers while collaborating with architects, product teams, developers, and stakeholders.

Lead end-to-end delivery of a Plant Performance Reporting transformation across manufacturing plants, manage executive stakeholders and governance, coordinate cross-functional and offshore teams, prioritize Snowflake data engineering and Power BI productionalization, oversee UAT and deployment, and drive adoption, training, and reporting standardization.

Embed with client engineering teams to deploy, integrate, and scale enterprise generative AI solutions. Build agentic systems, train and serve LLMs with Vertex AI, integrate models with BigQuery/AlloyDB/Spanner, implement streaming inference pipelines, and ensure operational reliability while collaborating with stakeholders to translate business goals into production-grade architectures.

Build high-performance API services and production-grade Generative AI systems. Design and implement end-to-end RAG pipelines, vector stores, embeddings, and latency-optimized generators. Develop agentic AI using LangChain/CrewAI/Semantic Kernel, integrate LLM APIs and AWS Bedrock, manage CI/CD and ML pipelines, and apply evaluation frameworks to detect hallucinations and optimize performance.

Lead and scale North America immigration operations, manage complex US and Canadian cases (H1B, PERM, L1, Express Entry, LMIA), ensure compliance, coordinate stakeholders and counsel, and track deadlines to deliver accurate, timely filings.

Lead end-to-end custodial data integrations from Tamarac into Salesforce, troubleshoot data and pipeline issues, and design/optimize Salesforce CRM workflows for wealth management. Serve as a hands-on SME, manage stakeholders, and deliver scalable solutions with minimal oversight.

The role involves managing large-scale data analytics projects, designing data solutions, and collaborating with executives to implement digital and cloud solutions.

The GenAI Engineer will design, build, and deploy Generative AI solutions, focusing on reinforcement learning and multi-agent workflows, while collaborating with various teams to enhance model performance.