Experience Level: 8+ Years Location: Flexible / Hybrid / Remote (as applicable) About the Role
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.
Key Responsibilities
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.
Required Qualifications
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.
Preferred Qualifications
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.
What We Offer
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