Tredence — a Bengaluru-based data-science and AI firm serving global enterprises — hires early-career Generative AI / LLM engineers to build RAG systems with LangChain, LlamaIndex and vector databases.
Disclaimer: This is a third-party opening shared for informational purposes. Cloud Soft Solutions is not the hiring employer; verify all details (eligibility, compensation, requisition IDs) on the official portal before applying.
Role Overview
Location: Bengaluru · Hybrid
Type: Generative AI / LLM (RAG) Engineer (early-career)
Experience: Early-career / freshers with a strong AI portfolio
Package: Competitive, as per Tredence norms (confirm on the official listing)
Key Highlights
- Build RAG systems with LangChain, LlamaIndex & vector DBs
- Generative AI / LLM engineering on enterprise data
- Bengaluru data-science & AI firm with global clients
- Early-career GenAI engineering roles
Eligibility & Skills
- B.E/B.Tech/M.Tech/MCA or equivalent
- Strong Python and ML fundamentals
- Hands-on with RAG, LangChain/LlamaIndex, embeddings and vector databases (e.g., ChromaDB)
- A public GitHub portfolio of GenAI/RAG projects
How to Apply
Check current openings and apply on the official Tredence Careers page (also on LinkedIn). Lead with your GitHub and shipped RAG projects.
Pro tips: for AI-first companies your GitHub portfolio is your resume — ship real projects (a working RAG app, an agentic workflow with LangGraph/CrewAI, a fine-tuned or prompt-engineered LLM demo), write clean READMEs, and reference them in every application.
How to Prepare for This Role
Build RAG, LangChain and vector-database skills; prepare with our RAG interview questions, Agentic AI Engineer roadmap and AI & ML interview questions.
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Want to Crack Agentic AI & RAG Roles Confidently?
Cloud Soft Solutions (Hyderabad, with live-online batches across India) offers hands-on AI/ML + Generative & Agentic AI training — Python, LLMs, RAG (LangChain, LlamaIndex, vector databases), agentic frameworks (LangGraph, CrewAI, AutoGen), real projects, interview preparation and proven placement support.
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Frequently Asked Questions
Who can apply for early-career GenAI / RAG engineer roles at Tredence?
Early-career candidates and freshers with a B.E/B.Tech/M.Tech/MCA, strong Python and ML fundamentals, hands-on RAG experience (LangChain/LlamaIndex, embeddings, vector databases like ChromaDB) and a public GitHub portfolio of GenAI/RAG projects.
How do I apply to Tredence for GenAI / RAG engineer roles?
Check current openings on the official Tredence careers page (tredence.com/careers) and its LinkedIn listings. Lead your application with a GitHub portfolio of RAG projects.