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Full time 🤖 AI / ML

Senior AI Engineer at Workato

Listed by DevShelfHub

Hyderabad, India
Hybrid
Mid-level · 3–5 yrs

About the Role

Workato is hiring a Senior AI Engineer on its Enterprise Retrieval team in Hyderabad. You will build the retrieval layer that powers enterprise AI agents — stitching together Salesforce, Zendesk, Jira, SharePoint, and more into ranked, permission-aware responses.

Workato delivers enterprise infrastructure for the agentic era, trusted by 50% of the Fortune 500.

What you'll do

  • Build unified retrieval layer across enterprise systems with agent-friendly interface
  • Design hybrid retrieval pipelines with smart re-ranking for cross-source results
  • Engineer incremental sync pipelines with low latency and predictable cost
  • Ensure permission-aware retrieval mirroring source-system ACLs exactly
  • Build query understanding — intent parsing, entity linking, LLM-assisted rewriting
  • Design chunking and embedding strategies for docs, tickets, conversations, records
  • Build evaluation and experimentation harnesses for retrieval and agent answers
  • Ship observable production systems with strong SLOs and dashboards
  • Mentor teammates on retrieval architecture and evaluation rigor

What we're looking for

  • 3-5 years building production search, retrieval, knowledge-base, or recommendation systems
  • Strong proficiency in Python, Go, Java, or similar backend language
  • Hands-on experience with OpenSearch, Elasticsearch, Solr, or Vespa
  • Solid IR fundamentals: TF-IDF, BM25, learning-to-rank, query parsing, relevance evaluation

Skills & Technologies

Required

3-5 years building production search, retrieval, knowledge-base, or recommendation systems Strong proficiency in Python, Go, Java, or similar backend language Hands-on experience with OpenSearch, Elasticsearch, Solr, or Vespa Solid IR fundamentals: TF-IDF, BM25, learning-to-rank, query parsing, relevance evaluation Working experience with vector search — FAISS, pgvector, Pinecone, Weaviate, Qdrant, Milvus Experience designing or contributing to RAG pipelines and semantic search in production Familiarity with transformer embeddings, cross-encoder re-rankers, LangChain, LlamaIndex

Benefits & Perks

  • Health Insurance
  • Flexible Leave Policy
  • Learning Budget
  • EPF / NPS

Why This Role is Good for Experienced Professionals

  • Go deep on retrieval quality where classical IR, dense vectors, knowledge graphs, and LLM reasoning collide.
  • Build unified retrieval layer across Google Drive, SharePoint, Confluence, Jira, Salesforce, and more
  • Design hybrid pipelines combining BM25, dense vector, and structured retrieval
  • Engineer ingestion and freshness pipelines for millions of documents and records
  • Own permission-aware retrieval (ACL preservation) across enterprise systems
  • Build query understanding for agents — intent parsing, entity linking, query rewriting
  • Design chunking and embedding strategies per content type
  • Build evaluation harnesses — NDCG, MRR, recall@k, faithfulness, citation accuracy
  • Ship production-grade systems with SLOs on latency, freshness, recall, and cost
  • Hands-on Senior IC role with direct enterprise impact
  • Flexible, trust-oriented culture with innovation focus

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, Workato's cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale.
Industry
Technology
Company Size
500+
Website
workato.com
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Job Details

Type
Full time
Level
Mid-level
Experience
3–5 years
Location
Hyderabad, India
Work Mode
Hybrid
Category
AI / ML

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