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Job Description : We are seeking an experienced Python Technical Lead with strong AI and machine learning expertise to drive the development of high-quality, scalable software solutions. This role blends advanced Python engineering skills with hands-on AI capabilities. You will architect, build, and optimize backend services, automation pipelines, AI-driven applications, and data workflows while guiding a growing engineering team. Responsibilities: Lead the design and development of robust, scalable Python applications, APIs, microservices, and automation workflows. Architect clean, maintainable, and modular codebases using Python best practices. Build data processing, ETL, and feature engineering pipelines supporting AI/ML workloads. Optimize systems for performance, reliability, and scalability. Work with DevOps pipelines to automate testing, deployment, and monitoring of Python and AI services. Ensure robust CI/CD workflows and production readiness. AI / Machine Learning Integration: Work with Azure AI services (Cognitive Services, Computer Vision, NLP, Speech, ML Studio) to build intelligent applications. Implement ML models using Python frameworks such as TensorFlow, PyTorch, Scikit-learn, FastAPI, and MLFlow. Integrate AI components into production-grade Python applications. Evaluate new AI tools/libraries beyond Azure when appropriate. Technical Leadership: Provide hands-on technical leadership throughout the SDLCarchitecture, design, development, testing, deployment, and maintenance. Review and guide the work of junior developers, promoting coding standards and engineering best practices. Work closely with cross-functional teams to translate business requirements into actionable technical solutions. Stay updated on advancements in Python, AI frameworks, cloud practices, and MLOps techniques. Identify opportunities to incorporate modern AI techniques or optimize current architecture. Robust expertise in: Python (Flask, Django, FastAPI, asyncio) Data processing frameworks (Pandas, NumPy, PySpark) Cloud platforms (Azure preferred) Practical experience integrating AI/ML into applications (NLP, CV, ML models). Hands-on experience with TensorFlow, PyTorch, Scikit-learn, etc. Strong understanding of Agile, DevOps, and CI/CD processes. Excellent communication, leadership, and problem-solving skills. Preferred: Experience with Microsoft Azure Technology. Experience deploying AI models in production environments. Exposure to vector databases, LLM applications, or GenAI frameworks. Knowledge of MLOps tools such as MLFlow, Kubeflow, or Azure ML pipelines. Exposure to agentic architectures, including tool-using agents, planning agents, or multi-agent workflows. Familiarity with MCP (Model Context Protocol) building MCP servers, exposing tools, or integrating agents with MCP. Experience developing RAG (Retrieval-Augmented Generation) pipelines and .
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.