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Position Summary We are seeking a proactive and technically strong Data Science & GenAI Production Support Engineer to provide production support for our Data Science and Generative AI solutions. The ideal candidate will be responsible for ensuring the stability, reliability, and performance of AI and data science applications while driving root cause analysis, continuous improvements, and AI-enabled operational efficiencies. Key Responsibilities Provide production support for Data Science and Generative AI applications. Monitor, troubleshoot, and resolve production issues within defined SLAs. Perform root cause analysis (RCA) for incidents and implement preventive measures. Support deployment, maintenance, and optimization of data science models in production. Work closely with Data Scientists, AI Engineers, and Platform teams to ensure smooth production operations. Develop automation and operational improvements to enhance support efficiency. Leverage AI tools and technologies to improve support workflows and accelerate issue resolution. Contribute to AI proof of concepts (POCs) and identify opportunities to integrate AI into operational processes. Maintain operational documentation, knowledge articles, and support runbooks. Participate in on-call support and incident management activities as required. Required Skills Experience in Data Science Model Production Support. Strong understanding of Root Cause Analysis (RCA) and production incident management. Hands-on experience with Neo4j. Knowledge of Agentic AI concepts and applications. Strong proficiency in Python, PySpark, and SQL. Experience with the Microsoft Azure data ecosystem, including: Azure Databricks Azure Data Factory (ADF) Azure Data Lake Storage (ADLS) Ability to troubleshoot data pipelines and production data issues. Strong analytical, problem-solving, and communication skills. Familiarity with MLOps and model lifecycle management is an added advantage. .
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.