Senior Software Engineer - Integrations - AI/ML

In this Senior Software Engineer role, you own and evolve ClickHouse’s AI ecosystem, bridging high-performance database engineering with developer tooling. You’ll build production-grade Python connectors and SDKs, enabling data scientists and engineers to harness ClickHouse in AI pipelines, RAG workflows, and real-time ML applications. You’ll shape integration patterns with LangChain, LlamaIndex, and broader AI tooling, delivering tangible impact for millions of developers and AI-powered data systems. You’ll work across open-source communities and internal teams to raise reliability and performance.

• Flexible work environment, remote-friendly
• Healthcare contributions
• Equity and stock options
• Flexible time off
• Home office setup stipend ($500)
• Global company gatherings

• Own and evolve ClickHouse's Python connector and SDK ecosystem, improving performance, reliability, and API design
• Drive AI/LLM integration strategy by designing connectors and patterns for RAG, ML feature pipelines, and LLM-powered data apps
• Engage with the open-source community: triage issues, support contributors, advocate for users, shape roadmap
• Collaborate with Product, Cloud, and other engineering teams to align integration work with platform priorities
• Ground roadmap decisions in real-world Data Engineer and Data Scientist workflows

• 7+ years of software development experience
• Deep experience designing, building, and maintaining production-grade Python connectors/SDKs/integrations for a major platform
• Hands-on AI/ML in production data-engineering contexts (embedding generation, vector search, feature pipelines)
• Strong Python data ecosystem knowledge (Pandas, NumPy, Pydantic)
• Solid SQL and OLAP/database fundamentals; data modeling and query optimization
• Experience with concurrent Python (threading, multiprocessing, async)
• Excellent written and verbal communication; cross-functional collaboration with open-source
• Bonus: prior Data Engineer/Data Scientist experience in product-facing roles; familiarity with ClickHouse or JVM; experience deploying AI/ML models in production; exposure to dbt, Airflow, Dagster, Prefect

• strong communication
• cross-functional collaboration
• pragmatic, practitioner-focused decision-making
• Python connectors/SDK development
• AI/ML in production data contexts (embedding, vector search)
• Pandas, NumPy, Pydantic