Senior GenAI Engineer – Agentic AI, Databricks

This is a fully remote position, open to applicants in Romania.

📋 Description

• Define the architecture of GenAI solutions and jointly take ownership of technical decisions from the initial design phase to production delivery.

• Create, construct, and manage AI agents for data collection, indexing, and market intelligence.

• Incorporate LLMs, prompts, and tools into dependable end-to-end workflows.

• Develop and sustain data pipelines and lakehouse architectures in Databricks.

• Ingest, transform, and structure both structured and unstructured data for AI-driven applications.

• Create ontologies that categorize domain concepts and relationships to support agent reasoning.

• Connect AI agents with Databricks data and functionalities.

• Analyze Databricks Genie and custom agent frameworks while assisting in defining integration architecture.

• Develop and manage Python components for web scraping, content extraction, and indexing.

• Evaluate tools, frameworks, and implementation strategies, driving enhancements across architecture, codebase, and engineering practices.

• Engage in brainstorming sessions, design reviews, and project delivery.

• Articulate technical decisions, constructively challenge assumptions, and share insights on implementation.

⛳️ Requirements

• Senior-level engineering experience with responsibility for complex technical solutions from architecture and design to production delivery.

• Proficient Python engineering skills with the capability to develop reliable, maintainable production code.

• Practical experience in building GenAI applications, which includes LLM integration, agentic frameworks, and prompt and tool orchestration.

• Strong data engineering background involving the construction of pipelines and processing both structured and unstructured data.

• Hands-on experience with Databricks, covering lakehouse structures, notebooks, and workflows.

• Excellent architectural judgment, capable of assessing trade-offs and making decisions with limited information.

• Delivery-oriented approach with technical ownership and active implementation involvement.

• Technology-agnostic perspective, able to evaluate, adopt, and switch tools, agent frameworks, and platforms as needed.

• Strong collaboration and communication abilities.

• Experience with knowledge graphs or ontology-based modeling.

• Background in creating scalable web scraping and crawling solutions.

• Familiarity with Databricks Genie or agent frameworks that integrate with data platforms.

• Experience in market intelligence, competitive analysis, or content indexing.

• History of shaping architecture for early-stage or greenfield projects.

🏝️ Benefits

• Medical benefits

• Gym support

• Personalised fitness options

• Team events

• Healthy Habits Club

• Flexible work-life dynamic

• Mental wellbeing support

• Social wellbeing activities and community connection

• Hybrid work environment