AI Engineer Data Engineer

We love technology, and we enjoy what we do. We are constantly driven by curiosity, innovation, and the desire to improve every day. We take ownership of our work, value collaboration, and foster a culture of trust and accountability. Our Enroute rs embrace challenges, ask questions, learn quickly, and grow together.

We pride ourselves on offering competitive compensation, excellent benefits, a great work environment, flexible schedules, and policies that promote a healthy work-life balance. We care about who you are both inside and outside the workplace, and we are committed to building a strong community of driven, responsible, respectful—and above all—happy individuals. We want you to genuinely enjoy working with us.

We are seeking a data-driven Ai Engineer to join our team at a high-growth advertising technology company. This role focuses on scaling our reporting infrastructure for advertising performance and billing reconciliation, ensuring that financial and operational data is accurate, automated, and actionable.

In this role, you will be responsible for developing robust data pipelines, ensuring data quality and reliability, and enabling efficient data consumption across the organization. You will collaborate closely with cross-functional teams including Product, Engineering, Analytics, and Business stakeholders to deliver high-impact data platforms.

The ideal candidate is a proactive problem-solver with strong technical expertise, capable of working with large datasets, modern data architectures, and cloud-based environments. You thrive in fast-paced settings, navigate ambiguity with confidence, and are passionate about turning data into actionable value.

Requirements

Databricks & AI Architecture (Must-Have)

• Strong experience working with Databricks Lakehouse architecture
• Nice to have expertise in Databricks Mosaic AI and Unity Catalog for governing AI assets
• Hands on experience Building RAG (Retrieval-Augmented Generation) pipelines using Vector Search

SQL & Data Modeling (Must-Have)

• Advanced SQL development

AI Engineering & Data Workflows (Must-Have)

• Experience integrating LLM APIs (OpenAI, Anthropic, etc.) into data workflows
• Hands-on experience using AI for:
• Data enrichment
• Anomaly detection
• Automated classification
• Experience with LangChain, LlamaIndex, or similar frameworks
• Exposure to Model Context Protocol (MCP) or similar approaches to connect AI models with external tools and data sources
• Strong understanding of Tool Calling / Function Calling : enabling LLMs to interact with SQL databases and external APIs securely.
• Experience in Prompt Engineering and Guardrailing : designing system prompts that maintain context and hierarchy (e.g., understanding team associations).