Workato
Workato

23 Workato Staff Engineer Jobs Hiring Near You

Responsibilities As we work towards building out the Context Layer for the Agentic Enterprise, we are looking for an exceptional Search/AI Engineer with experience in Search Relevance to join our ...

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Workato Jobs Information

What is it like to work at Workato?

Workato is a collaborative and innovative company that prioritizes teamwork, creativity, and customer satisfaction. The company's structure is designed to foster a sense of community, with a flat organizational hierarchy and cross-functional teams working together to drive product development and customer success. As a company that empowers businesses to automate and integrate their workflows, Workato offers a dynamic and challenging work environment that appeals to candidates who are passionate about technology, innovation, and problem-solving.

What makes Workato an attractive place to work?

Workato is a leading enterprise automation platform that enables businesses to integrate and automate their workflows, positioning itself at the forefront of the digital transformation landscape. The company fosters a workplace culture that values innovation, collaboration, and continuous learning, with a focus on delivering cutting-edge solutions to its customers. By joining Workato, professionals can contribute to shaping the future of automation and enjoy opportunities for growth, skill development, and making a meaningful impact in the industry.

What are the most popular categories at Workato?

Infographic showing various Staff Engineer job openings at Workato in the United States as of August 2026, with employment types broken down into 2% Internship, and 98% Full Time. Highlights an 31% Physical, and 69% Remote job distribution.

Full-time

Re-posted 18 days ago


Job description

Responsibilities

As we work towards building out the Context Layer for the Agentic Enterprise, we are looking for an exceptional Search/AI Engineer with experience in Search Relevance 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.

In this role, you will also be responsible for:

  • Lead the development of advanced query understanding systems that parse natural language, resolve ambiguity, and infer user intent

  • Design and 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

  • Create and maintain graph-based knowledge systems that enhance LLM capabilities through structured relationship data

  • Drive improvements in query rewriting, intent classification, and semantic search, using both statistical and neural methods

  • Own the design of evaluation frameworks for offline/online relevance testing, A/B experimentation, and continual model tuning

  • 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

RequirementsQualifications / Experience / Technical Skills
  • Bachelor's/Master's/PhD degree in Statistics, Mathematics, 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

  • Proficiency in Knowledge Graph construction and optimization is a plus

  • Strong analytical and problem-solving skills

Soft Skills / Personal Characteristics
  • Strong communication abilities to explain technical concepts

  • Collaborative mindset for cross-functional teamwork

  • Detail-oriented with strong focus on quality

  • Self-motivated and able to work independently

  • Passion for solving complex search problems

(REQ ID: 2472)