Senior Software Engineer (Search / Retrieval)

Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com

Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company. 

But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. 

If this sounds right up your alley, please submit an application. We look forward to getting to know you!

Also, feel free to check out why:

• Business Insider named us an “enterprise startup to bet your career on”

  
  

• Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world

  
  

• Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America

  
  

• Quartz ranked us the #1 best company for remote workers

  
  

We are looking for an exceptional Senior Software Engineer (Search / Retrieval) to join our growing team. In this role, you will lead the design, development, and optimization of intelligent search systems that leverage machine learning at their core. You’ll be responsible for building end-to-end retrieval pipelines that incorporate advanced techniques in query understanding, ranking, and entity recognition. The ideal candidate combines deep expertise in information retrieval and search relevance with hands-on experience applying machine learning to real-world search problems at scale. You will also be responsible to:

• Lead the development of advanced our search cluster that can scale to millions of documents across customers and data sources

  
  

• Deploy learning-to-rank models that optimize relevance using behavioral signals, embeddings, and structured feedback.

  
  

• Build and scale robust Entity Recognition pipelines that enhance document understanding, enable contextual disambiguation, and support entity-aware retrieval.

  
  

• Architect next-gen search infrastructure capable of supporting highly dynamic document corpora and real-time indexing.

  
  

• Drive improvements in query construction, indexing and search performance

  
  

• Be up-to-date with the latest improvements in search and indexing technologies

  
  

• Collaborate with product and applied research teams to translate user needs into data-informed search innovations

  
  

• Produce clean, scalable code and influence system architecture and roadmap across the relevance and platform stack.

  
  

• Bachelors/Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field.

  
  

• 7+ years of backend engineering experience with 3+ years in search, information retrieval, or related fields

  
  

• Strong proficiency in Python

  
  

• Hands-on experience with search engines (Opensearch or Elasticsearch)

  
  

• Strong understanding of information retrieval concepts spanning traditional methods (TF-IDF, BM25) and modern neural search techniques (vector embeddings, transformer models)

  
  

• Experience with text processing, NLP, and relevance tuning

  
  

• Experience with relevance evaluation metrics (NDCG, MRR, MAP)

  
  

• Experience with large-scale distributed systems

  
  

• Strong analytical and problem-solving skills

  
  

• Strong communication abilities to explain technical concepts

  
  

• Collaborative mindset for cross-functional team work

  
  

• Detail-oriented with strong focus on quality

  
  

• Self-motivated and able to work independently

  
  

• Passion for solving complex search problems