Senior GenAI Engineer (Agentic AI & Databricks)
- Compensation
- Not disclosed
- Location
- Employees can work remotely, ro
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- 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
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
Full description
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 approache
ResponsibilitiesAI 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
Must Have
- Senior-level engineering experience, with demonstrated ownership of complex technical solutions from architecture and design through production delivery