Senior/Staff Software Engineer, Search & Retrieval Infrastructure
New
Based in the United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 6+ years
- Required Skills
- PythonJavaKubernetesC++GoRust
Requirements
- 6+ years of experience building production-grade backend systems in large-scale distributed environments.
- Strong expertise in system architecture, with a focus on high throughput, low latency, and scalable design principles.
- Experience building or working with search systems, including semantic search, vector databases, hybrid retrieval, or platforms like Elastic or OpenSearch.
- Deep understanding of retrieval-augmented generation (RAG), embedding pipelines, and LLM-based orchestration patterns.
- Proficiency in at least one major programming language such as Go, Rust, C++, Java, or Python.
- Experience with data engineering and building large-scale indexing pipelines for diverse data types.
- Familiarity with modern infrastructure tools such as Kubernetes, cloud-native architectures, observability systems, and IaC tools like Terraform or Pulumi.
- Strong product mindset with the ability to design developer-friendly and agent-friendly APIs.
- Comfortable working in ambiguous, high-growth environments with significant ownership expectations.
- Strong problem-solving skills and a bias toward building robust, long-term systems rather than short-term fixes.
Responsibilities
- Design and build scalable search and retrieval infrastructure, including semantic search, hybrid retrieval, metadata-aware querying, and LLM-driven query planning systems.
- Develop high-throughput indexing pipelines for both structured and unstructured data, ensuring performance, reliability, and scalability.
- Build and maintain backend services that support retrieval orchestration, knowledge synthesis, and agentic AI workflows.
- Improve retrieval quality through robust evaluation frameworks, observability systems, and experimentation on ranking and relevance.
- Design clean, intuitive, and scalable APIs for both internal systems and external developer and agentic use cases.
- Optimize system performance across latency, throughput, and cost in large-scale distributed environments.
- Drive technical direction for reliability, security, and architectural evolution of core retrieval systems.
- Collaborate closely with cross-functional teams to align infrastructure capabilities with product and AI application needs.
- Contribute to system-level design decisions that shape long-term platform scalability and extensibility.
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