Senior Software Engineer - Professional Archive Search & AI - Smarsh

As a Senior Software Engineer on the Professional Archive Search team, you’ll help design, build, and evolve advanced search and data systems that power our platform. Your work will focus on blending traditional search with modern AI-driven approaches, including vector search, knowledge graphs, and retrieval-augmented generation (RAG).

You’ll play a key role in enabling Smarsh clients to meet their compliance needs by delivering scalable, reliable, and high-performance search capabilities. This includes working with high-dimensional data, real-time pipelines, and hybrid search systems.

You’ll collaborate with cross-functional partners across Product Management, Engineering, and Site Reliability to solve complex challenges and shape the future of search within our platform. We’re looking for someone who is thoughtful, curious, and excited to work at the intersection of search and AI.

How will you contribute?

• Support and empower your team by contributing to a collaborative, inclusive, and respectful work environment
• Partner with engineers and stakeholders to design and deliver scalable search and data solutions
• Help bridge traditional lexical search and modern semantic search approaches
• Design and implement hybrid search strategies combining keyword-based and vector-based retrieval
• Work with vector databases to manage and query high-dimensional embeddings
• Design and optimize retrieval-augmented generation (RAG) pipelines, including handling long documents and retrieval quality
• Contribute to knowledge graph–driven approaches to enhance search relevance and data relationships
• Build and maintain high-throughput streaming data pipelines (e.g., Kafka) for real-time ingestion and indexing
• Contribute to architectural decisions that improve system scalability, reliability, and observability
• Participate in a shared on-call rotation to support service reliability and incident response with a focus on learning and prevention
• Collaborate with Product and Engineering to define technical requirements, timelines, and deliverables
• Apply modern engineering practices, including Agile methodologies, CI/CD pipelines, and DevOps principles
• Review code, identify areas for improvement, and help reduce technical debt
• Troubleshoot and resolve production issues to maintain high availability and performance
• Stay current with emerging technologies in search, AI, and data systems, and evaluate their impact
• Deploy and manage applications in Kubernetes environments
• Monitor application health and performance using tools such as Splunk, Datadog, and Grafana

What will you bring?

We’re looking for someone who enjoys working collaboratively, values continuous learning, and communicates openly and respectfully. You support others, share knowledge, and contribute to an inclusiv