Fresh job postings across Bengaluru, Hyderabad, Pune and Gurugram spiked this weekend, with employers urgently seeking Agentic AI, Retrieval‑Augmented Generation, and LLM operations skills. Students and early professionals eyeing GenAI roles can still apply before Monday screenings. Multiple boards show “posted today” or “1 day ago” stamps across agent and RAG listings in these cities.
What stands out in descriptions is depth, not buzzwords. Recruiters want hands‑on LangChain or LangGraph, vector databases, and secure deployments on Azure OpenAI or AWS Bedrock. Representative ads explicitly call for multi‑agent orchestration, workflow engines, RAG infrastructure, and governance guardrails, signaling production expectations beyond prototypes.
Agentic AI, RAG and Azure OpenAI roles: where the openings are today
Verified weekend examples include Bengaluru’s Tredence “Senior AI Engineer – Agentic AI Platform” posted “1 day ago”; Hyderabad’s Tachyon Technologies “Sr AI ML Engineer” requiring Microsoft Agent Framework and Azure OpenAI; Pune’s Haparz “Senior AI/ML Engineer (AWS Bedrock)” with remote option; and Gurugram’s Accenture “AI/ML Engineer” posted within the last 24 hours.
GenAI salary bands and remote options
Indicative weekend CTC ranges from live salary trackers suggest mid‑career spreads have widened. Bengaluru still commands a premium, while several Pune listings note hybrid or remote flexibility. Use these bands as negotiation anchors, then adjust for company tier, domain sensitivity, and on‑call expectations. See guide below.
| Experience | Indicative CTC (LPA) | Notes |
|---|---|---|
| 3–5 years | 10–25 | Bengaluru skew; startups may pay higher |
| 6–9 years | 20–40 | Premium for LLMOps and platform work |
| 10–12 years | 28–45 | Architecture, governance, multi‑agent at scale |
Ranges triangulate recent Bengaluru reports and India‑wide guides; several show medians near ₹10–21 LPA with ceilings rising for GenAI specialists and startups. Cross‑check against role level and city before committing.
LLMOps, LangChain‑LangGraph, Azure OpenAI, AWS Bedrock: quick‑apply checklist
Tailor a one‑page resume highlighting shipped RAG systems and cost controls. Link a concise repo showing LangGraph or LangChain agents with evals. Mention vector choices and guardrails. Add brief notes on Azure OpenAI or Bedrock deployment steps. Keep availability clear for Monday calls, and enable job‑board quick apply.
Monday timelines, screenings and what interviewers ask now
Expect rapid screens from 10 a.m. Monday, often before shortlists lock. Be ready to explain retrieval design, chunking, reranking, and budget guardrails. Describe LLMOps pipelines for prompts, configs, and observability. Share one outage post‑mortem and one latency win. If hybrid, confirm office days early to avoid offer delays.
