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We are looking for an AI Engineer specializing in Agentic AI systems and cloud-native deployment. This role focuses on building intelligent, autonomous systems using LLMs, RAG architectures, and emerging protocols like MCP, with an emphasis on scalable, production-ready implementations. Experience: 5 years - Minimum 5 years of experience is required. Location: Hybrid - Bengaluru/ Hyderabad/ Pune/ Gurugram Shift Timings: 12 PM - 9 PM IST Looking for immediate joiners only Key Responsibilities Design and build Agentic AI systems capable of planning, reasoning, and tool usageDevelop and optimize RAG (Retrieval-Augmented Generation) pipelines for enterprise use casesImplement and integrate Model Context Protocol (MCP) or similar frameworks for tool orchestrationBuild multi-agent workflows and autonomous decision-making systemsDeploy AI applications on cloud platforms (AWS, Azure, GCP) with scalability and reliabilityDevelop APIs and services to integrate LLM-powered features into productsWork with vector databases and retrieval systems for efficient knowledge accessOptimize latency, cost, and performance of LLM-based applicationsImplement observability, monitoring, and evaluation frameworks for AI systemsCollaborate with product and engineering teams to deliver production-grade AI solutions Required Skills & Qualifications 5+ years of experience in software engineering or AI engineering rolesStrong proficiency in Python and modern backend frameworks (FastAPI, Flask, etc.)Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or similarStrong understanding of RAG architectures, embeddings, chunking, and retrieval strategiesExperience with vector databases (Pinecone, Weaviate, FAISS, Chroma, etc.)Experience building agentic workflows (tool use, memory, planning, orchestration)Familiarity with MCP (Model Context Protocol) or similar tool-interaction paradigmsExperience deploying AI applications on cloud platforms (AWS/Azure/GCP)Strong knowledge of Docker, Kubernetes, and microservices architectureExperience designing and consuming REST APIs / async systems Preferred Qualifications Experience with multi-agent systems and orchestration frameworksFamiliarity with prompt engineering, evaluation, and guardrailsKnowledge of LLM observability tools (LangSmith, Weights & Biases, etc.)Experience with streaming architectures and real-time AI systemsExposure to security and governance in AI systemsUnderstanding of cost optimization strategies for LLM usage Soft Skills Strong problem-solving and system design skillsAbility to work in fast-evolving AI landscapesGood communication and cross-functional collaboration .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.