Senior AIML Data Engineer

As a Principal Solution Consultant, you will be the primary technical strategist for our most complex, high-stakes enterprise engagements. You will bridge the gap between sophisticated Data Engineering architectures and cutting-edge AI/ML applications to solve real-world business challenges. This is a high-impact role requiring a blend of deep technical "hands-on-keyboard" expertise and executive-level storytelling. Key Responsibilities Technical Discovery & Strategy: Lead deep-dive discovery sessions to uncover client pain points. Translate messy data landscapes into elegant, scalable AI/ML roadmaps. Architectural Design: Design end-to-end data architectures—from ingestion and transformation (ETL/ELT) to model deployment (MLOps) and visualization. Cross-Functional Leadership: Act as the "voice of the customer" for Product and Engineering teams to influence the product roadmap based on market feedback. Trusted Advisor: Build long-term relationships with CTOs, CDOs, and Lead Data Scientists, guiding them through the complexities of AI governance, ethics, and scalability. Requirements Technical Requirements Data Engineering (Mastery): 8+ years of experience with distributed systems (Spark, Flink), modern data stacks (Snowflake, Databricks), and orchestration tools (Airflow, dbt). AI/ML Expertise: Proven experience deploying ML models into production. Deep understanding of the ML lifecycle (MLOps), vector databases (Pinecone, Milvus), and fine-tuning Large Language Models (LLMs). Cloud Infrastructure: Expert-level proficiency in at least one major cloud provider (AWS, Azure, or GCP), specifically around data and AI services (e.g., SageMaker, Vertex AI). Architecture: Experience designing microservices-based architectures and API integrations. Travel Flexibility Flexbilit of travelling to client sites. You thrive in face-to-face environments where high-touch technical strategy and relationship building are key to executing complex deals. #J-18808-Ljbffr