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About the position We are looking for a remote Mid-Level AI Engineer with hands-on experience building and deploying Generative AI solutions. This is an engineering role focused on developing production-ready applications using Large Language Models (LLMs), RAG, and cloud AI platforms such as AWS Bedrock or OpenAI APIs. This is not a research-focused position. Responsibilities Implement retrieval-augmented generation techniques to customize LLMs for practical business use. Use AWS Bedrock, OpenAI or similar APIs to embed generative AI into existing systems. Build AI-powered tools to enhance operational efficiency, decision-support systems, or customer workflows in industry settings. Work with data engineering to preprocess and manage data for model inputs, ensuring security and compliance. Monitor and refine LLM deployments in scalable, reliable environments. Collaborate with software engineers, product managers, and stakeholders to deliver AI solutions that meet real needs. Create clear documentation and explain technical concepts to both technical and non-technical audiences in a hands-on context. Requirements Professional experience developing applications in Python. Hands-on experience building or deploying LLM-based applications. Experience with RAG, OpenAI/AWS Bedrock APIs, or similar GenAI frameworks. Experience integrating AI solutions into production or business applications. Strong English communication skills. 13 years (or more) of applied experience in Software, Data, or ML Engineering (e.g., backend, data pipelines, model implementation). Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn). Familiarity with AWS, GCP, or Azure integration. Interest in LLMs, prompt engineering, RAG, and applied AI, demonstrated through project work or prior deployments. Ability to take a project from prototype to delivery, optimizing for performance and business value. Clear communication, cross-functional collaboration, agile mindset. Nice-to-haves Experience with LLM fine-tuning, prompt engineering, or LangChain/Agent frameworks. Familiarity with MLOps tools (e.g., MLflow, Docker, CI/CD pipelines). Industry-specific experience (e.g. maritime, logistics, finance) is a bonus, but we prioritize applied engineering experience over domain knowledge. Apply To this Job Company : Umanova SA Salary : Work from home .
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.