We’re a team of 500+ professionals who develop cutting-edge proxy and web data scraping solutions for thousands of the world’s best known businesses, including Fortune 500 companies.
What’s in store for you:
You’ll be solving complex challenges and maintaining our own infrastructure with 60PB+ monthly data traffic. Here are its scale and maturity in numbers:
- 6PB+ Ceph storage
- 60PB+ monthly data traffic through our systems
- 300k+ service requests/sec processed
- 500k+ Kafka messages/sec streamed
The team waiting for you:
We’re building the AI layer on top of one of the world’s largest B2B data platforms. Our product lets users ask questions in plain language and get data-driven answers from millions of company and professional records. Think of it as giving our dataset a brain.
We’re forming a dedicated squad to take this from promising product to industry-leading platform. If you’re a Python developer who’s been itching to go deep on LLMs, RAG, and agentic AI — not just toy projects, but production systems at scale — this is your chance. You’ll work alongside experienced Staff Engineers, ship to real customers, and help define how AI reshapes B2B data intelligence. We have a seat ready for you!
### In this role, you’ll:
Design, develop, and maintain Python backend services powering our AI products.
Build and optimize LLM-powered pipelines — RAG, semantic search, natural language query processing.
Develop agent workflows and tool-use patterns for the AI Data Assistant.
Integrate with large-scale data infrastructure — vector databases, search engines, and analytical query engines.
Design and implement API endpoints to serve AI-generated insights to client-facing products.
Optimize prompt engineering, LLM output quality, and system reliability.
Collaborate with cross-functional teams (Data Engineering, API, Client Side) to deliver product features.
Monitor and improve performance, latency, and cost efficiency of AI services.
Contribute to evaluation frameworks and testing strategies for AI-powered features.
Share knowledge and help build the team’s collective expertise in applied AI.
### Your skills & experience:
2+ years of professional backend development experience.
Experience building and deploying production-grade APIs.
Familiarity with LLM APIs (OpenAI, Anthropic, or similar) — professional or personal projects.
Understanding of retrieval-augmented generation (RAG) patterns or strong willingness to learn.
Experience working with databases — relational (PostgreSQL/MySQL) and/or search engines (Elasticsearch).
Experience with Docker and containerized environments.
Strong problem-solving skills and genuine curiosity about AI technologies.
Ability to work with ambiguity and evolving requirements in a fast-moving product space.
### Nice to have:
Experience with vector databases (Qdrant, Pinecone, Weaviate).
Experience with LLM orchestration frameworks (LangChain, LlamaIndex).
Experience with agent/tool-use patterns and agentic programming.
Data engineering background — Kafka, Spark, Trino, dbt, or similar.
Experience with prompt engineering and LLM evaluation.
Experience with Kubernetes.
Familiarity with observability tools (Grafana, Sentry, OTel).
Understanding of NLP concepts (embeddings, semantic similarity, tokenization).
Up for the challenge? Let’s talk!
