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Cloud & AI Backend Engineer (GenAI / LLMOps) Own Cloud | Build and Scale AI Systems Location: Onsite / Hybrid (India) About Us BidWiser a next-gen, AI-powered SaaS platform that is revolutionizing how engineering companies handle tenders and proposals. Our team is passionate about blending cloud-native architecture, Generative AI, and LLMOps into scalable, production-ready tools . We operate in a large, under-digitized multi-billion- dollar market with strong early traction. Role Overview We are hiring a Cloud & AI Backend Engineer (GenAI / LLMOps) to own Bidwiser's cloud infrastructure and AI backend end-to-end . This is a hands-on, ownership-driven role not limited to DevOps or ML research. You will manage AWS and Azure deployments, optimize cost and performance, build and scale LLM-powered systems, and collaborate closely with founders and product teams as we grow. What You'll Own End-to-end ownership of AWS and Azure infrastructure AWS: ECS, EC2, Lambda, S3, CloudWatch, IAM, VPC Azure equivalents where applicable Manage and improve CI/CD pipelines (GitHub Actions, infra automation) Monitor, optimize, and control cloud costs proactively Own production deployments, uptime, reliability, and incident resolution Build, deploy, and scale AI backend services used by real customers Develop and maintain LLM-powered features across the product Design and optimize RAG pipelines , embeddings, vector search, and inference layers Fine-tune models (LoRA / adapters / prompt tuning where applicable) Collaborate closely with frontend, product, and founders Support rapid experimentation and production rollout of AI features What We're Looking For 23 years of relevant work experience in Cloud and AI Systems. Strong hands-on experience with AWS cloud services Working knowledge of Azure or strong willingness to own it Experience managing production SaaS infrastructure Proven experience deploying LLMs or ML models in production Strong backend engineering skills ( Python preferred ) Experience with FastAPI / Flask or similar frameworks Understanding of LLMOps / MLOps / AI system design Experience with vector databases and AI pipelines Ability to debug production issues and own outcomes end-to-end Startup Mindset & Ownership: Thrives in a fast-paced startup environment, comfortable wearing multiple hats, takes full ownership of outcomes, is willing to stretch beyond fixed hours when needed, enjoys hands-on problem solving, and is genuinely interested in growing long-term with the company while building core systems from the ground up. What We Offer Opportunity to own the entire cloud and AI backend stack Work on real-world GenAI systems used by enterprise customers Direct collaboration with founders and leadership Steep learning curve across cloud, AI, and distributed systems ESOPs for long-term contributors Learn from the best in the industry Apply on Linkedin and submit your resumes here: .
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.