Sr Data & AI Engineer

We are seeking a highly experienced Senior Data & AI Engineer to design, build, and scale modern data platforms and AI-driven solutions. This role sits at the intersection of data engineering, machine learning, and generative AI, with a strong focus on building reliable, production-ready systems that power analytics, intelligent applications, and LLM-based solutions.

You will work closely with data scientists, product teams, and business stakeholders to deliver high-impact data and AI capabilities on cloud-native architectures.

• Design, develop, and maintain scalable data pipelines and data platforms using modern data engineering and cloud-native tools.
• Build and optimize data models, data warehouses, and lakehouse architectures to support analytics and AI workloads.
• Develop and deploy machine learning and AI solutions, including LLM-powered applications and AI-driven analytics.
• Integrate large language models (LLMs), including OpenAI models, into enterprise data and application workflows.
• Implement structured output and orchestration frameworks (e.g., Pydantic, LangChain) to support reliable LLM pipelines.
• Collaborate with data scientists to productionize ML models using frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Develop and optimize SQL and Spark workloads on platforms such as Databricks.
• Support data visualization and BI solutions using tools like Power BI and/or Tableau.
• Apply best practices in CI/CD, version control (Git), automated testing, and agile software development.
• Evaluate and implement best-fit data architecture patterns, including Data Lakes, Data Mesh, Data Warehouses, and Lakehouse architectures.
• Ensure data quality, reliability, security, and governance across data and AI solutions.
• Mentor junior engineers and contribute to technical standards and architectural decisions.

• 8+ years of experience in data engineering, analytics engineering, or related technical roles.
• Strong programming skills in Python, with hands-on experience using ML frameworks such as TensorFlow, PyTorch, and/or Scikit-learn.
• Deep understanding of data modeling, data warehousing concepts, and large-scale data processing.
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
• Experience working with modern data platforms and warehouses, including Databricks.
• Proven experience building solutions using LLMs and generative AI, particularly with OpenAI APIs.
• Solid understanding of modern data architecture patterns (Data Lake, Data Mesh, Data Warehouse, Lakehouse).
• Experience with BI and data visualization tools such as Power BI and/or Tableau.
• Familiarity with structured output tooling and LLM orchestration frameworks (e.g., Pydantic, LangChain).
• Experience with CI/CD pipelines, Git-based version control, and agile development practices.

• Experience with Spark, Delta Lake, or similar distributed data processing technologies.
• Knowledge of MLOps practices and tools for model deployment and monitoring.
• Exposure to real-time or streaming data architectures.
• Strong communication skills and experience working with cross-functional teams.

• Opportunity to work on cutting-edge data and generative AI initiatives.
• Influence over technical architecture and platform direction.
• Collaborative, growth-oriented engineering culture.
• Competitive compensation and benefits package.

Equal Opportunity Employer, including disability and protected veteran status