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Role Overview We are seeking an experienced AI Forward Deployment Engineer (AI FDE) to design, develop, and deploy production-grade AI/ML solutions in collaboration with customers and internal engineering teams. This role requires a strong combination of software engineering expertise, AI/ML implementation experience, cloud-native development skills, and the ability to translate complex business requirements into scalable, real-world AI applications. The ideal candidate is a hands-on technical expert who thrives in fast-paced environments, can architect solutions while remaining deeply involved in coding, and has experience taking AI/ML systems from concept through production deployment and ongoing optimization. Key Responsibilities Design, develop, and deploy end-to-end AI/ML applications that solve complex business problems. Translate architectural designs and technical requirements into scalable, production-ready implementations. Build and integrate AI/ML capabilities into enterprise applications using modern frameworks, APIs, and software engineering practices. Develop scalable AI systems leveraging microservices, APIs, event-driven architectures, and cloud-native technologies. Perform hands-on implementation across the AI/ML lifecycle, including data preparation, model integration, application development, deployment, debugging, and optimization. Work with structured and unstructured data sources to build robust AI-driven solutions. Design, implement, and optimize AI workloads on cloud platforms such as Azure or AWS. Apply strong software engineering practices including version control, CI/CD, monitoring, logging, testing, and production support. Collaborate with customers, product teams, and engineering teams to rapidly prototype, deploy, and improve AI solutions. Act as a technical owner for assigned solutions, ensuring reliability, scalability, and operational readiness. Required Qualifications 6+ years of professional experience in designing and developing AI/ML applications (maximum 15+ years overall experience). Strong hands-on programming experience in Python with the ability to design and implement production-grade solutions. Experience with JavaScript/Node.js or .NET/C# is a plus. Proven experience in software architecture and system design, with the ability to translate concepts into working code. Strong hands-on development mindset, with the expectation of spending 50–70% of time coding and implementing solutions . Practical experience building AI/ML solutions end-to-end, including: Data preparation and processing Model integration and evaluation Application development and deployment Production troubleshooting and optimization Experience with AI/ML frameworks such as Scikit-learn, TensorFlow, and/or PyTorch . Experience designing and building scalable AI systems using APIs, microservices, and event-driven architectures. Strong data engineering skills with hands-on experience using Pandas, NumPy , and working with structured and unstructured datasets. Experience deploying and supporting AI workloads in cloud environments such as Microsoft Azure or AWS . Strong understanding of DevOps and production engineering practices, including: Git-based development workflows CI/CD pipelines Logging and monitoring Application performance tuning Production support and debugging
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.