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Position Overview We are looking for a Senior AI/ML Engineer to design, implement, and integrate AI and Machine Learning solutions across the Microsoft Fabric/Databricks ecosystem. The role will focus on developing AI/ML use cases, establishing secure end-to-end data and AI connections, and integrating enterprise data sources with Claude and Nexus AI platforms. The ideal candidate has strong hands-on experience with MCP (Model Context Protocol) Server installation and configuration, enterprise data integration, AI/ML model development, and security and governance. The position will involve working with a U.S.-based client, so fluent English is mandatory. Key Responsibilities Design and develop AI/ML use cases leveraging Microsoft Fabric and Databricks platforms. Install, configure, and maintain MCP Servers to enable secure integration between enterprise data sources and AI platforms. Establish end-to-end source and target connections between: Microsoft Fabric Gold Layer Salesforce SAP ECC Claude Platform Nexus AI Build, train, deploy, and optimize AI and Machine Learning models based on business requirements. Design data flows and integration patterns connecting enterprise data sources to AI/ML applications. Configure authentication, authorization, security controls, and governance for AI/ML environments. Ensure data access and AI integrations comply with enterprise security, privacy, and governance standards. Collaborate with data engineers, architects, business stakeholders, and AI/ML teams to translate business requirements into scalable technical solutions. Troubleshoot integration, connectivity, model, and deployment issues across the AI/ML technology stack. Contribute to technical architecture, implementation standards, and best practices for enterprise AI adoption. Required Skills & Experience Strong experience in AI/ML engineering and production implementation. Hands-on experience with Microsoft Fabric and/or Databricks. Experience designing and implementing AI/ML use cases on enterprise data platforms. Hands-on experience installing and configuring MCP Servers. Experience establishing end-to-end source and target connections using MCP. Experience integrating enterprise systems and data sources such as: Microsoft Fabric Gold Layer Salesforce SAP ECC Experience integrating AI platforms, particularly Claude and/or Nexus AI. Experience building and deploying Machine Learning and AI models. Strong understanding of data integration, APIs, connectivity, and enterprise data architectures. Experience implementing security, access controls, governance, and authentication for AI/ML solutions. Ability to troubleshoot complex integration and connectivity issues. Strong understanding of enterprise AI architecture and data flows. Fluent in english. Preferred Qualifications Experience with Model Context Protocol (MCP) architecture and ecosystem. Experience with Anthropic Claude or similar enterprise AI platforms. Experience with Nexus AI or comparable AI platforms. Experience working with SAP and Salesforce enterprise environments. Knowledge of cloud-based AI/ML architectures and deployment patterns. Experience with MLOps, model lifecycle management, and production AI deployments. Knowledge of data governance, responsible AI, and enterprise security frameworks. Core Technical Focus The successful candidate will be responsible for delivering an end-to-end architecture in which MCP Servers securely connect enterprise source systems, including the Fabric Gold Layer, Salesforce, and SAP ECC, with target AI platforms such as Claude and Nexus AI, while enabling the development and deployment of AI/ML use cases on Fabric and Databricks. Seniority Senior-level engineering role requiring strong hands-on technical expertise, independent problem-solving capabilities, and the ability to work across data, AI/ML, integration, security, and governance domains.
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.