Senior Software Engineer - Integrations - AI/ML
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Position Overview & Specifications
About ClickHouse
Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 4,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.
The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.
We’re on a mission to transform how companies use data. Come be a part of our journey!
The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.
Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.
What you'll do
- Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
- Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
- 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
About you
- 7+ years of software development experience, including hands-on time as a Data Engineer, Data Scientist, or ML Engineer
- 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
- Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
- Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
- Solid experience with concurrent Python: threading, multiprocessing, and async patterns
- Outstanding written and verbal communication; comfortable collaborating across e
The Connectors team is the bridge between ClickHouse and the broader ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide, from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.
Our work directly shapes how companies process massive datasets: real-time analytics platforms that ingest millions of events per second, observability systems that monitor global infrastructure, and, increasingly, AI-powered data applications that redefine how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.
About the role
As a Senior Software Engineer specialising 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.
We're looking for someone who has firsthand experience as an AI & MLEngineer or Data Scientist. 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.
What you'll do
- 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
About you
- 7+ years of software development experience, including hands-on time as a Data Scientist or ML Engineer
- 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
- Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
- Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
- Solid experience with concurrent Python: threading, multiprocessing, and async patterns
- Outstanding written and verbal communication; comfortable collaborating across engineering functions and with open-source communities
Bonus points for:
- 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
Compensation
For roles based in the United States, the typical starting salary range for this position is listed above. In certain locations, such as the San Francisco Bay Area and the New York City Metro Area, a premium market range may apply, as listed.
These salary ranges reflect what we reasonably and in good faith believe to be the minimum and maximum pay for this role at the time of posting. The actual compensation may be higher or lower than the amounts listed, and the ranges may be subject to future adjustments.
An individual’s placement within the range will depend on various factors, including (but not limited to) education, qualifications, certifications, experience, skills, location, performance, and the needs of the business or organization.
If you have any questions or comments about compensation as a candidate, please get in touch with us at
Candidate Selection & Onboarding Process
Application & Resume Screening
Submit your tailored CV/Resume directly to the talent acquisition portal.
Technical & Competency Interviews
Virtual interviews with the hiring manager and multidisciplinary team.
Formal Offer & Benefits Negotiation
Written agreement outlining compensation, equity, retirement vesting, and relocation allowances.
Onboarding & Corporate Integration
Equipment provisioning, team orientation, and commencement of duties.
United States Work Authorization & Sponsorship Guide
Under United States immigration law (INA § 101(a)(15)(H)), foreign nationals seeking full-time professional positions typically navigate either non-immigrant specialty occupation classifications or immigrant visa sponsorship:
Requires a relevant Bachelor's degree or higher. Employers must file an approved Labor Condition Application (LCA) with the US Department of Labor confirming the prevailing wage rate.
Canadian and Mexican citizens qualify under USMCA (TN status). F-1 STEM graduates benefit from 36-month aggregate work authorization through E-Verify enrolled employers.
Candidate Preparation Blueprint: Technology
Based on transatlantic hiring benchmarks for Senior Software Engineer - Integrations - AI/ML roles across clickhouse's corporate sector, successful applicants typically excel across three core dimensions:
Demonstrated portfolio evidence, architecture/system design case studies, or validated professional certifications directly applicable to Technology.
STAR method competency responses highlighting cross-functional leadership, conflict resolution, and delivering measurable enterprise ROI under tight timelines.
Total compensation expectation aligned within the benchmarked Salary Disclosed on Application bracket, including retirement vesting and health parity.
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