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RAG Engineer — Cohere India
T1
Cohere

RAG Engineer — Cohere India

Cohere is hiring RAG Engineers for India operations. ₹40-80 LPA. Bengaluru / remote. Eligibility: 3+ years building retrieval-augmented systems. Required: deep embedding + retrieval expertise, vector databases (Weaviate / Qdrant / Pinecone), LLM application architecture, producti
private-mnc
RAG Engineer
mid
hybrid

ટૂંકમાં: Cohere India seeks RAG Engineers (₹40–80 LPA, Bengaluru/remote) with 3+ years building retrieval-augmented systems. Expertise in vector databases, embeddings, and LLM architecture required. Direct application via Cohere careers portal.

About this RAG Engineer role at Cohere

Cohere, a leader in generative AI and LLM technology, is building its India operations and seeking RAG Engineers in Bengaluru. This is a mid-level position for experienced AI engineers who want to work on retrieval-augmented generation systems at scale—a core competency in modern LLM applications. Based in Bengaluru with hybrid flexibility, this role puts you at the center of AI infrastructure innovation.

What you'll do

  • Design and optimize retrieval-augmented generation (RAG) pipelines that combine LLMs with external knowledge sources for improved accuracy and relevance.
  • Work with vector databases like Weaviate, Qdrant, or Pinecone to manage embeddings and implement efficient semantic search at scale.
  • Develop and fine-tune embedding models that power retrieval quality, ensuring relevance and performance in production environments.
  • Build LLM application architectures that integrate retrieval systems, prompting strategies, and response generation into cohesive production systems.
  • Deploy and monitor RAG systems in production, managing performance, latency, and cost optimization across real-world workloads.
  • Collaborate with cross-functional teams to implement information retrieval best practices and improve model performance iteratively.

Who should apply

You need 3+ years of hands-on experience building retrieval-augmented systems or similar AI infrastructure. This is a mid-level role—not entry-level—so you should have shipped production AI systems before. Deep expertise in embeddings and vector databases is essential; familiarity with at least one of Weaviate, Qdrant, or Pinecone is expected. You understand LLM application architecture and deployment challenges. If you're a senior engineer with this background, you're absolutely welcome to apply; Cohere values strong technical depth.

Salary & offer in context

Cohere offers ₹40–80 LPA (₹3,33,333–₹6,66,667 per month), positioning this role in the upper-mid band for AI engineer salaries in India. For a RAG Engineer in Bengaluru with 3+ years experience at a private MNC, this reflects market rates for specialized AI infrastructure roles—particularly at a company betting heavily on LLM capabilities.

Path to apply

This is a direct online application through Cohere's careers portal—no exam, no gatekeeping process. You apply directly to Cohere and move through their standard technical interview process. The application deadline is 13 June 2026, so if this role interests you, apply within the next two weeks. Cohere typically moves quickly on hiring for India operations.

એક નજરે

Sector
Private-mnc
Apply કેવી રીતે
Online-portal
Role
RAG Engineer
Experience
Mid
સેલેરી
₹333333 – ₹666667/મહિનો
Location
Bengaluru
કામ કરવાની વ્યવસ્થા
Hybrid
છેલ્લી તારીખ
2026-06-13T00:00:00.000Z
છેલ્લી વાર ચકાસાયું
2026-06-12T00:00:00.000Z

RAG Engineer માટે અરજી કરવા પહેલાં Free Courses

આ role માટે AIshala-ચકાસાયેલ free courses અહીં છે, ક્રમમાં. કુલ સમય: 6 અઠવાડિયા.

પગલું 1
AI ના મૂળ શીખો
Covers RAG architecture, retrieval pipelines, and LLM integration—the core concept for this role.
પગલું 2
બનાવો અને શીખો
Teaches production deployment, scaling, and monitoring of LLM applications—essential for Cohere's infrastructure focus.
પગલું 3
આત્મવિશ્વાસ સાથે Apply કરો
Provides hands-on patterns for embeddings, vector search, and prompt engineering in real-world RAG systems.

ઘણાને પૂછ્યું જાય છે

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