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29 changes: 1 addition & 28 deletions src/features/careers/components/CareersPage.jsx
Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ import { MapPin, Briefcase, ChevronDown, ExternalLink } from 'lucide-react';
import Navbar from '../../home/components/Navbar';
import Footer from '../../home/components/Footer';

const APPLY_URL = 'https://docs.google.com/forms/d/e/1FAIpQLSfTqBrU9bQVcrkCdpeRdkl1Z5s55ZEzpkl261TszvbFqo9q6g/viewform';
const APPLY_URL = 'https://forms.gle/PZAZ9rVnYcZvUxx97';

const jobPostings = [
{
Expand Down Expand Up @@ -58,33 +58,6 @@ const jobPostings = [
'A track record of contributions to open-source AI projects',
],
},
{
title: 'RAG Engineer',
experience: '1–3 years',
about: "Build production-ready RAG systems that leverage Bodhan AI's models for Indian language applications. Work on LangChain, LlamaIndex, and custom orchestration frameworks.",
responsibilities: [
"Design and implement RAG pipelines using Bodhan AI's speech and LLM models",
'Optimize retrieval systems for multilingual document search (22 Indian languages)',
'Build vector databases and embedding systems for Indian languages',
'Develop prompt engineering strategies for Indian language LLMs',
'Create production-ready APIs and integration examples',
],
required: [
'1–3 years experience with LLMs and RAG systems',
'Hands-on experience with LangChain, LlamaIndex, or similar frameworks',
'Proficiency in Python and modern ML frameworks',
'Experience with vector databases (Pinecone, Weaviate, ChromaDB, FAISS, Milvus)',
'Understanding of embedding models and semantic search',
],
preferred: [
'Experience with multilingual RAG systems',
'Knowledge of Indian languages',
'Built production RAG systems serving real users',
'Familiarity with Bodhan AI models',
'Experience with prompt optimization and chain-of-thought reasoning',
'Contributions to RAG-related open-source projects',
],
},
{
title: 'System Architect',
experience: '5–10+ years',
Expand Down
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