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We are looking for a talented Backend Engineer to join our team, working on backend systems that power cutting-edge AI applications. This role focuses on API integration, AWS DevOps, and building scalable systems to handle large-scale workloads. If you're passionate about backend engineering, AI integration, and tackling challenges at scale, we'd love to hear from you! Responsibilities AI Model API Integration Build and maintain pipelines to integrate custom AI models hosted on Hugging Face via REST APIs. Optimize API calls for cost efficiency and peak performance. Pipeline Development Design, implement, and maintain scalable, fault-tolerant pipelines for real-time and batch processing workflows. Manage data preprocessing and postprocessing workflows for AI models. AWS DevOps Deploy and manage infrastructure using AWS services: EC2, S3, RDS, spot fleets, auto-scaling groups, load balancers, and CloudFormation. Optimize GPU instance workloads at scale (hundreds of machines in parallel). Configure custom AMIs and implement auto-scaling strategies tailored to operational needs. System Scalability & Monitoring Build backend systems capable of managing large parallel workloads with minimal downtime. Monitor and optimize system performance using AWS CloudWatch. Collaboration Work closely with machine learning engineers, full-stack engineers, and other team members to ensure seamless integration and operational excellence. Requirements Technical Skills Proficiency in Python. Experience with REST API integration. Solid understanding of AWS services: EC2, S3, RDS, CloudFormation, spot fleets, and auto-scaling groups. Hands-on experience with Docker. Expertise in cost optimization and performance tuning for GPU workloads. Strong SQL skills (NoSQL knowledge is a plus). Experience Proven track record of building scalable backend systems and AI/ML application pipelines. Experience managing real-time and batch processing workflows. Familiarity with monitoring tools like AWS CloudWatch. Ideally AWS Certified Soft Skills Strong problem-solving abilities and ability to work independently. Excellent communication skills for cross-functional collaboration. Why Join Us? Work on groundbreaking AI projects that solve real-world problems across diverse industries. Be part of a high-impact team, leveraging cutting-edge technologies to build scalable systems at scale. Collaborate with a talented and passionate team of engineers. If you're ready to take on challenging backend engineering problems in the AI space, apply now!
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.