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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.

What Youll be Doing:

Data Pipelines at Scale
Own end-to-end architecture and delivery of our 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.

We're looking for an Infrastructure Engineer to go deep into that layer: build and own core proxy and networking infrastructure, not configure someone else's.

You bring the same range as our core infrastructure engineers - proxies and networking, browser internals, and cloud-native systems (Kubernetes, Docker, AWS) - with the depth to design and debug at every layer of the stack, plus a genuine specialization in networking and proxy systems.

What Youll be Doing:
Build core proxy infrastructure - reverse proxies, IP rotation, session management, intelligent routing.
Own IP pool health - reputation scoring, monitoring, blacklist recovery - across residential, mobile, datacenter, and ISP proxies.
Implement geo-targeting at country, city, and ASN level.
Work at the protocol level (TCP/UDP, sockets, HTTP/HTTPS/SOCKS5, HTTP/2/3) and the Linux networking stack underneath.
Build monitoring, health checks, failover, and bandwidth/usage metering for the proxy fleet.
Deploy and scale on cloud-native infrastructure (Kubernetes, Docker, Terraform).
Use AI-assisted development tools daily.

We're looking for a Senior Backend Engineer to own core infrastructure that powers our platform - from the pipelines that move and process data at scale, to the systems that keep our engineering org shipping fast and reliably. This is a technical leadership role: you'll set architecture direction, raise the bar on engineering practices, and mentor other engineers, while staying deeply hands-on.

You'll operate in an organization that expects AI-native ways of working. Using tools like Claude, Cursor, Hermes or LangGraphor isn't a bonus here - it's the baseline for how we build, and we expect you to help the rest of the team level up on it too.

What Youll be Doing:
Own core backend infrastructure - design and build scalable, reliable Node.js/TypeScript/Python/Go services that other teams and systems depend on.
Build and scale data pipelines - architect the infrastructure that processes and moves large volumes of data reliably, efficiently, and at scale.
Elevate test & validation infrastructure - build the automation, tooling, and CI/CD systems that let engineering ship fast without breaking things, and that make quality and reliability measurable.
Set technical direction - make architecture decisions with company-wide impact, drive design reviews, and establish engineering standards and best practices.
Mentor and multiply - level up other engineers technically, and help shape a fast, high-ownership engineering culture as the team grows.
Lead with AI-native workflows - use AI-assisted development tools daily to move faster without sacrificing architectural quality, and champion their adoption across the team.