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Sr. Software Engineer - Professional Archive Search & AI

Smarsh

Remote · United StatesFull Time$125k–$155k

Sr. Software Engineer - Professional Archive Search & AI at Smarsh is a full time role based in Remote · United States (remote). The listing states pay of $125k–$155k. It was published on 27 July 2026 and was open at last check.

Sr. Software Engineer - Professional Archive Search & AI at Smarsh — key details
RoleSr. Software Engineer - Professional Archive Search & AI
CompanySmarsh
LocationRemote · United States (remote)
Employment typeFull Time
Pay (as listed)$125k–$155k
Published27 July 2026
StatusOpen at last check

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 inclusive and positive team culture.

  • Experience building and operating software in a modern private cloud-based environment
  • Strong background in distributed systems and search or data-intensive applications
  • Experience with search technologies such as Lucene, Elasticsearch, or Solr, including how indexing and query systems work
  • Hands-on experience with vector similarity search and vector databases (e.g., Qdrant, Milvus, Vespa, or similar)
  • Familiarity with retrieval-augmented generation (RAG) concepts and architectures
  • Understanding of knowledge graphs or graph-based data modeling concepts
  • Experience designing scalable data pipelines and working with streaming technologies such as Kafka
  • A collaborative mindset, with openness to feedback and different perspectives
  • Understanding of modern software development practices and Agile methodologies
  • Ability to communicate technical concepts, progress, and trade-offs clearly
  • Comfort working in evolving environments where requirements may change over time
  • A proactive and thoughtful approach to solving complex problems

Preferred Qualifications

  • Around 6+ years of experience in software engineering, with experience in search or data systems
  • Proficiency in Java or a similar backend programming language
  • Experience deploying and managing applications in Kubernetes
  • Familiarity with relational databases and query optimization (e.g., MS SQL or similar)
  • Experience working with Linux-based systems
  • Exposure to messaging systems such as Kafka or AMQ
  • Experience contributing to or designing AI/ML-powered systems in production environments
  • Participation in open-source projects or technical communities
  • The ProArchive Application Development team embraces an AI-first mindset, continuously elevating developer productivity through tools like GitHub Copilot, Windsurf, and Claude Code. We’re seeking developers who are passionate about advancing their AI-assisted development skills and leveraging them to deliver innovative, high-impact solutions for Smarsh customers.

What do we offer?

Healthcare insurance: We provide medical, dental, and vision insurance, and a flexible spending account that allows you to set aside pre-tax dollars to pay for eligible out-of-pocket expenses. Stock options. Personal time off: A healthy work-life balance is critical to your success at the office. Smarsh offers a “take-what-you-need” time off policy as well as flexible work arrangements. 401K Match: Smarsh provides a 4% 401K match for which employees are fully vested on day one. Sabbatical: The Smarsh sabbatical programme provides a time to recharge, study or simply do something you are passionate about away from the workplace. Employees are eligible after six years of service. Recognition: We’re big on kudos for a job well done. Our employee-recognition programme enables co-workers to nominate their peers who best embody our core values for recognition.

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Sr. Software Engineer - Professional Archive Search & AI at Smarsh — questions answered

What does the Sr. Software Engineer - Professional Archive Search & AI role at Smarsh pay?

The Sr. Software Engineer - Professional Archive Search & AI at Smarsh listing states pay of $125k–$155k for the Remote · United States (remote) position. That figure is taken directly from the employer's own posting as published, not estimated or averaged from other roles.

Is the Sr. Software Engineer - Professional Archive Search & AI role at Smarsh remote?

Yes — Smarsh advertises this Sr. Software Engineer - Professional Archive Search & AI role as remote, tied to Remote · United States, and it is listed as full time work. Remote terms come from the employer's own posting, so confirm the expected working hours, timezone and any on-site days with Smarsh before you apply.

Is the Sr. Software Engineer - Professional Archive Search & AI role at Smarsh still open?

The Sr. Software Engineer - Professional Archive Search & AI posting at Smarsh was open at OnJob's last check of the employer's careers page, having been published on 27 July 2026. OnJob re-checks source listings on each build and marks a role closed once it disappears, but listings can close without notice, so the employer's own page is the final word.

How do you apply for the Sr. Software Engineer - Professional Archive Search & AI role at Smarsh?

Apply to the Sr. Software Engineer - Professional Archive Search & AI at Smarsh role through OnJob with a free profile: OnJob scores your fit against the listing, shows the skills lowering that score, and submits an ATS-ready profile to Smarsh's own application page. Creating a profile is free and needs no card.

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