Senior Software Engineer (Integrations, Artificial Intelligence/Machine Learning)

• As a Senior Software Engineer specializing in the AI & ML ecosystem, you’ll be a core contributor owning and evolving critical parts of ClickHouse’s AI ecosystem
• This role sits at the intersection of high-performance database engineering and developer experience
• You’ll craft tools that enable Engineers and Data Scientists to harness ClickHouse’s speed and scale in the frameworks they already use
• The data practitioner’s world is shifting rapidly: databases are no longer just query targets, but they’re becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference
• You understand these workflows not from the outside, but because you’ve operated within them. You don’t just build integrations, you bring product-level insight into what we should build and why
• You’ll own the full lifecycle of key AI/ML integrations, driving architecture, performance, and feature direction across AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications
• ClickHouse’s columnar architecture and query performance make it exceptionally well-positioned in this new landscape
• Your job is to make that potential real: building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems
• Own and evolve ClickHouse’s Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Drive the AI/LLM integration strategy: designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner’s perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

Benefits

• Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in 20 countries
• Healthcare - Employer contributions towards your healthcare
• Equity in the company - Every new team member who joins our company receives stock options
• Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites
• Time off - Flexible time off in the US, generous entitlement in other countries
• A $500 Home office setup if you’re a remote employee- We’re looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• 7+ years of software development experience, including hands-on time as a Data Scientist or ML Engineer
• Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Outstanding written and verbal communication; comfortable collaborating across engineering functions and with open-source communities
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Hands-on experience applying AI/ML in production data-engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling that shipped and ran in production
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem
• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Familiarity with tools like dbt, Airflow, Dagster, Prefect is a plus