Software Engineer - II

Role Overview

The Ecosystem team at Yugabyte is responsible for building, maintaining and strengthening the ecosystem around YugabyteDB - integrations with other tools/frameworks, ensuring compatibility, enabling third-party partners, developing connectors, driving community adoption, and helping Yugabyte fit seamlessly into the broader data / cloud / AI stack.

You will work across internal product, engineering, documentation, and partner teams to make sure Yugabyte is well supported in the ecosystem, that customers and partners have high-quality integrations, and that Yugabyte can be plugged into many use cases with minimal friction.

Key Responsibilities

• Develop, maintain, and test integrations/connectors between YugabyteDB and popular data ecosystem tools (e.g. ORM frameworks, Spark, Presto, Kafka, etc.).


• Ensure compatibility with client-side APIs, drivers (JDBC, Python, Go, Rust, C#, etc.), ORMs, data pipelines, and analytic tools.


• Stay updated with the evolving AI ecosystem (LLMs, frameworks like LangChain, LlamaIndex, etc.) for integration opportunities.


• Evaluate ecosystem requirements and gaps: identify which integrations would add most value to customers and partners.


• Collaborate with the product & engineering teams to specify integration requirements, define interfaces/APIs, and ensure that the product supports ecosystem use cases.


• Partner with partner teams, community, and external developers to enable partner use-cases, build partner / third-party contributions.


• Own end-to-end quality of integrations: functional correctness, performance, deployment, configuration, and documentation.


• Write sample applications, SDKs, reference architectures, and demonstrations to show how to use Yugabyte with other technologies.


• Contribute to, or own documentation / best practices / how-to guides related to integrations and ecosystem use cases.


• Monitor and keep abreast of relevant big-data / cloud / data tools trends, new platforms, and emerging technologies; propose ecosystem enhancements.

Skills & Qualifications

Required

• Strong programming skills in one or more languages like C, C++, Java, Python, Go, Rust, C#, etc.


• Deep understanding of distributed database concepts (sharding, replication, consistency, scaling).


• Experience with building connectors/integrations between databases and other systems (analytics tools, ORMs, caching, message brokers, etc.).


• Familiarity with client driver protocols/APIs (JDBC, REST, gRPC, etc.).


• Understanding of AI concepts like vector search, retrieval-augmented generation (RAG)


• Experience working in Linux / Unix environments; comfortable with command-line, debugging, etc.


• Good software engineering fundamentals: testing, performance, reliability, version compatibility.


• Strong communication skills, ability to collaborate across teams (product, engineering, documentation, partners).

Nice to Have

• Hands-on experience with big data tools like Apache Spark, Presto, Flink, Kafka.


• Experience with cloud platforms (AWS, GCP, Azure) and containerization / Kubernetes.


• Experience with ORMs, frameworks (SpringData, Hibernate, Django, etc.).


• Experience with LLM integration and AI orchestration frameworks (LangChain, LlamaIndex, or similar).


• Prior open source contributions or experience engaging with the community.


• Experience building sample integrations / reference architectures.

Pluses / Distinguishing Points

• Ability to proactively spot ecosystem gaps and propose solution / proof-of-concept.


• Experience working with partner / ISV / cloud provider programs.