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About Us Deccan AI Experts is a pioneering AI company founded by IIT Bombay and IIM Ahmedabad alumni, with a strong founding team from IITs, NITs, and BITS. We specialize in high-quality human-curated data, AI-first operations, and advanced AI evaluation systems. Our global network of AI and infrastructure experts helps train and evaluate next-generation AI models through expert systems engineering, search infrastructure expertise, and large-scale distributed systems knowledge. About the Role We are seeking a Search Infrastructure Engineer (Freelancer) to support advanced AI evaluation initiatives focused on search infrastructure, indexing systems, information retrieval, vector search, search relevance, distributed systems, and AI-generated technical content evaluation. In this role, you will evaluate AI-generated search architectures, indexing pipelines, retrieval workflows, ranking strategies, search optimization techniques, vector database integrations, and technical documentation. Your expertise will help improve AI systems designed for enterprise search, Retrieval-Augmented Generation (RAG), semantic search, and large-scale information retrieval. This position is ideal for professionals with experience in search engineering, search infrastructure, distributed systems, information retrieval, AI infrastructure, backend engineering, or search platform development. About the Responsibilities - Review AI-generated indexing pipelines, search architectures, ranking algorithms, retrieval workflows, query optimization strategies, API designs, and system documentation. - Evaluate search platforms involving full-text search, semantic search, hybrid search, vector databases, document indexing, ranking, caching, and distributed retrieval. - Verify AI-generated recommendations for indexing strategies, search relevance tuning, latency optimization, scaling, monitoring, and production deployment. - Assess AI-generated solutions for maintainability, fault tolerance, observability, performance, and enterprise readiness. - Identify retrieval issues, indexing failures, ranking errors, scalability bottlenecks, infrastructure risks, and system design limitations. - Provide structured feedback to improve AI performance in search engineering, retrieval systems, and enterprise AI search platforms. - Review peer-developed deliverables to maintain quality and consistency standards. Requirements - Bachelor's degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Data Engineering, or a related field. - Master's degree is preferred. - 2+ years of hands-on experience in search engineering, backend engineering, distributed systems, information retrieval, AI infrastructure, or search platform development. - Building and maintaining enterprise search platforms. - Designing indexing pipelines and search architectures. - Optimizing search relevance, ranking, and query performance. - Developing scalable retrieval systems and APIs. - Reviewing AI-generated search infrastructure and technical documentation. - Proficiency in Java, Python, Go, C++, or Scala . - Familiarity with REST APIs, Kubernetes, Docker, Kafka, Redis, cloud platforms (AWS, Azure, Google Cloud), monitoring tools, and CI/CD pipelines. - Excellent analytical thinking, debugging, system design, documentation, and written English communication skills. - Solid attention to detail and ability to evaluate enterprise search solutions. - Ability to work independently in a remote, fast-paced environment. Preferred Qualifications - Experience working with large-scale search engines, AI platforms, e-commerce search, enterprise search, knowledge management systems, or cloud-native search infrastructure. - Experience implementing semantic search, hybrid search, Retrieval-Augmented Generation (RAG), recommendation systems, or AI-powered search platforms. - Experience evaluating AI-generated search architectures, indexing pipelines, ranking strategies, retrieval workflows, or technical documentation. - Familiarity with Generative AI, Large Language Models (LLMs), AI agents, AI benchmarking, RLHF (Reinforcement Learning from Human Feedback), LLMOps, or AI infrastructure is highly desirable. - Contributions to open-source search technologies or distributed systems projects are a plus. - Skilled certifications in cloud computing, Kubernetes, Elasticsearch, AI engineering, or distributed systems are advantageous. Why Join Us - Competitive hourly Compensation: 1,800/hour - Fully remote with flexible working hours. - Opportunity to contribute to cutting-edge AI initiatives in search infrastructure, semantic search, and Generative AI. - Exposure to advanced AI systems focused on Retrieval-Augmented Generation (RAG), enterprise search, vector search, and intelligent information retrieval. - Flexible project-based opportunities with global teams. - Work on next-generation AI solutions supporting enterprise software companies, AI .
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.