About Workato

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 Workatos 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

Why join us

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. Thats 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

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 this role you will lead the design development and optimization of intelligent search systems that leverage machine learning at their core. Youll 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 to:

• 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 inquery rewriting intent classification and semantic search using both statistical and neural methods.

• Own the design ofevaluation 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.

Requirements

Qualifications / Experience / Technical Skills

• 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

• 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 team work

• Detail-oriented with strong focus on quality

• Self-motivated and able to work independently

• Passion for solving complex search problems

For candidates based in California New York and Colorado the expected salary range for this role is $215000$285000. Actual compensation will vary based on experience qualifications and location. This role may also be eligible for equity and benefits.

(REQ ID: 2472)