Staff Data Scientist
Webflow
PythonSQL
Salary
💰 $151,500 - $215,500 per year
Job Level
Senior
Tech Stack
PythonSQL
About the role
- As a Lead AI Data Engineer on our Data Platform & Services (DPS) team, you’ll combine advanced data engineering expertise with cutting-edge AI practices to deliver production-grade systems that transform how Upwork uses data. You’ll design and deploy agentic frameworks, natural language querying (NLQ) solutions, and LLM evaluation strategies that make insights accessible at scale. This is a chance to deliver visible impact—accelerating decision-making, enabling self-service analytics, and empowering stakeholders across the company.
- Responsibilities:
- Design and implement scalable agentic frameworks that coordinate multiple AI agents to deliver accurate and reliable outcomes.
- Build and optimize natural language query systems that provide intuitive, compliant, and self-service access to enterprise data.
- Develop and maintain frameworks for evaluating prompts and LLMs, driving measurable improvements in accuracy, resilience, and scalability.
- Partner with data engineering peers to integrate AI orchestration with existing pipelines using Python, SQL, and Snowflake.
- Contribute to AI-powered summarization and explanation tools that enhance reporting, insights, and executive decision-making.
- Collaborate with product, analytics, and business teams to ensure AI solutions align with measurable business goals.
- What it takes to catch our eye:
- Proven success delivering AI-powered data systems in production, including hands-on experience with LLMs and prompt engineering.
- Strong foundation in modern data engineering with expertise in Python, SQL, and platforms such as Snowflake.
- Ability to design agentic orchestration frameworks that scale across diverse business scenarios.
- Collaborative problem-solver with excellent communication skills, able to align stakeholders and create clarity across teams.
- Growth mindset—eager to learn, iterate, and deliver measurable outcomes through applied AI.
Requirements
- Proven success delivering AI-powered data systems in production, including hands-on experience with LLMs and prompt engineering
- Strong foundation in modern data engineering with expertise in Python, SQL, and platforms such as Snowflake
- Ability to design agentic orchestration frameworks that scale across diverse business scenarios
- Collaborative problem-solver with excellent communication skills, able to align stakeholders and create clarity across teams
- Growth mindset—eager to learn, iterate, and deliver measurable outcomes through applied AI
