Senior GenAI Engineer (Agentic AI & Databricks)

About the Company
You'll join a team building an ecosystem of AI agents to automate knowledge-intensive workflows, from processing content at scale to generating insights from diverse data sources. The solution combines a modern lakehouse data platform with agentic AI and advanced knowledge modeling. The architecture is still evolving, and we're looking for a senior engineer to help shape it: someone who brings ideas, challenges assumptions, and takes ownership from technical decisions through delivery. We value a pragmatic, technology-agnostic approach. As the GenAI landscape evolves, you'll evaluate tools based on their strengths and fit for the problem, keeping an open mind about new approaches.
About the Role
We're looking for a senior engineer to help shape an evolving architecture for an ecosystem of AI agents and a modern lakehouse data platform, bringing ideas, challenging assumptions, and taking ownership from technical decisions through delivery, with a pragmatic, technology-agnostic approach to GenAI tools and methods.
Responsibilities
AI Architecture & Technical Ownership → Shape the architecture of GenAI solutions by proposing approaches, evaluating trade-offs, and co-owning technical decisions with the team, from initial design through production delivery.
AI Agent Development & Orchestration → Design, build, and orchestrate AI agents for data collection, indexing, and market intelligence, integrating LLMs, prompts, and tools into reliable end-to-end workflows.
Data Engineering & Lakehouse Development → Develop and maintain data pipelines and lakehouse structures in Databricks, supporting the ingestion, transformation, and organization of structured and unstructured data for AI-driven applications.
Knowledge Modeling & Ontology Development → Contribute to the knowledge-modeling layer by building ontologies that organize domain concepts and relationships, providing context to ground agent reasoning.
Agent Integration & Databricks Connectivity → Integrate AI agents with Databricks data and capabilities, evaluating approaches such as Genie and custom agent frameworks while helping define the integration architecture.
Python Development & Web Data Extraction → Build and maintain robust Python components for web scraping, content extraction, and indexing, ensuring reliable data collection and maintainable code.
Technical Evaluation & Continuous Improvement → Assess tools, frameworks, and implementation approaches. Identify and drive improvements across the architecture, codebase, and engineering practices as the solution evolves.
Technical Collaboration & Knowledge Sharing → Work closely with the team through brainstorming, design reviews, and delivery. Communicate technical decisions, challenge assumptions constructively, and share implementation insights.
Qualifications
5+ years of senior-level engineering experience, with demonstrated ownership of complex technical solutions from architecture and design through production delivery
Strong Python engineering skills, with the ability to develop reliable, maintainable production code
Hands-on experience building GenAI applications, including LLM integration, agentic frameworks, and prompt and tool orchestration
Solid data engineering experience, including building pipelines and processing structured and unstructured data
Practical experience with Databricks, including lakehouse structures, notebooks, and workflows
Strong architectural judgment, with the ability to evaluate trade-offs, make decisions with incomplete information, and translate technical direction into working solutions
A hands-on, delivery-focused approach, combining technical ownership with active implementation
A technology-agnostic mindset, with the ability to evaluate, adopt, and switch tools, agent frameworks, and platforms based on product needs and architectural requirements
Strong collaboration and communication skills, including the ability to explain technical choices and contribute constructively to design discussions
Required Skills
Strong Python engineering skills, with the ability to develop reliable, maintainable production code
Hands-on experience building GenAI applications, including LLM integration, agentic frameworks, and prompt and tool orchestration
Solid data engineering experience, including building pipelines and processing structured and unstructured data
Practical experience with Databricks, including lakehouse structures, notebooks, and workflows
Strong architectural judgment, with the ability to evaluate trade-offs, make decisions with incomplete information, and translate technical direction into working solutions
A hands-on, delivery-focused approach, combining technical ownership with active implementation
A technology-agnostic mindset, with the ability to evaluate, adopt, and switch tools, agent frameworks, and platforms based on product needs and architectural requirements
Strong collaboration and communication skills, including the ability to explain technical choices and contribute constructively to design discussions
Preferred Skills
Nice to Have
Experience with knowledge graphs or ontology-based modeling
Experience building scalable web scraping and crawling solutions
Familiarity with Databricks Genie or agent frameworks integrated with data platforms
Experience in market intelligence, competitive analysis, or content indexing
Experience shaping architecture for early-stage or greenfield projects

Work arrangement
Yes