Senior Team Lead - Data Pipelines & Agentic Web Extraction

Description:

We're looking for a Senior Team Lead to own two things at the core of our product: the data-pipeline infrastructure that ingests and processes web data at scale, and the agentic AI system that generates Extraction Templates - the mappings that turn any webpage into structured data.

You'll lead a team of 6 engineers spanning Backend, Full-Stack, and AI - coaching, managing, and hiring across both disciplines while staying hands-on, not just directing from a distance. Exceptional internal leadership and people skills are a must: clear communication and real ownership of team health, not just delivery.

Data Pipelines at Scale

• Own end-to-end architecture and delivery of Nimble's data-pipeline infrastructure - from system design to large-scale data flow, storage, and operations - already running in production for Fortune 500 customers.
• Continuously analyze and improve the efficiency, scalability, cost, and stability of pipeline components as volume grows by an order of magnitude or more.
• Design and implement supporting interfaces (Skills, Plugins, MCP, UI, API) and platform engineering where needed to deliver pipeline capabilities end-to-end.
• Partner closely with the Product and Delivery team to define and prioritize the right pipeline solutions.

Agentic Generation of Extraction Templates

• Bring deep, hands-on expertise in LLMs, agentic architectures, evaluation/benchmarking, and modern AI/LLMOps practices; make build-vs-buy and architecture calls with authority.
• Grow the team's AI capability day to day: actively promote and mentor AI-native development practices.
• Continuously improve the Extraction Template generation capability's coverage, accuracy, and scale

• 3+ years as a Team Lead across at least two workplaces, with strong leadership and people skills - clear communication and real ownership of team health. Comfortable operating independently without a dedicated PM, including direct customer communication.
• 6+ years as a Back-End engineer with high-scale, production data-pipeline experience - a data-engineering background is not required. Python is the primary language. able to architect solutions from scratch and deliver on time.
• Startup experience is a must; enterprise experience is a plus.
• Hands-on AI engineering experience: LLMs, agentic architectures, evaluation/benchmarking, prompt/context engineering.
• Genuine day-to-day AI usage; comfortable owning build-vs-buy/architecture calls; shipping an AI product in production is a plus.