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Job Title: Generative AI Python Engineer (GenAI Python Engineer) | Nineleaps | Bangalore / Hyderabad, India Recruiting Company: Nineleaps Job Location: Bangalore or Hyderabad, India Job Type: Full-Time | Hybrid Application Method: Send your updated CV to ana.bardhan@nineleaps.com Immediate Joiners Preferred Experience Required: 3-4 Years Hybrid Work Model Open to professionals with strong Generative AI and Python development experience Position Summary Nineleaps is seeking a talented Generative AI Python Engineer to design and build next-generation AI-powered applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. This role offers the opportunity to work on innovative AI solutions that transform business processes through intelligent automation, advanced analytics, and conversational AI technologies. Detailed Job Description As a GenAI Python Engineer, you will be part of a forward-thinking engineering team focused on delivering cutting-edge Artificial Intelligence solutions. You will design, develop, and optimize AI-driven applications using Python, REST APIs, vector databases, and cloud-native technologies on Google Cloud Platform (GCP). The position requires hands-on experience integrating Large Language Models through APIs, implementing RAG architectures, and developing intelligent agents capable of autonomous task execution. You will collaborate closely with product teams, solution architects, and data engineers to create scalable, reliable, and high-performance AI systems. This is an exciting opportunity for professionals passionate about Generative AI, machine learning innovation, and emerging AI technologies. Key Responsibilities Design and develop Generative AI applications using Python and modern AI frameworks Build and maintain scalable REST APIs using Flask and related backend technologies Implement Retrieval-Augmented Generation (RAG) architectures to enhance AI response accuracy Integrate and optimize Large Language Models (LLMs) through API-based interactions Develop Agentic AI solutions capable of autonomous and intelligent task orchestration Design, manage, and optimize vector database implementations for semantic search and retrieval Collaborate with cross-functional teams to define AI solution requirements and technical architecture Optimize application performance, scalability, security, and reliability across AI platforms Create and refine prompt engineering strategies to improve model outputs and business outcomes Deploy and manage AI workloads on Google Cloud Platform (GCP) Required Qualifications & Skills 3-4 years of professional software development experience with Python Strong expertise in Python programming and backend application development Hands-on experience building RESTful APIs using Flask or similar frameworks Solid understanding of SQL and database design principles Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions Strong knowledge of Large Language Models (LLMs) and AI model integration techniques Experience with Agentic AI frameworks and autonomous AI workflows Familiarity with vector databases and semantic search technologies Experience with Prompt Engineering and AI model optimization Hands-on experience deploying applications on Google Cloud Platform (GCP) Strong problem-solving, analytical thinking, and collaboration skills Ability to work effectively in agile development environments Nice-to-Have Skills Experience with FastAPI for high-performance API development Knowledge of LangChain, LlamaIndex, or similar GenAI orchestration frameworks Experience with Docker and Kubernetes containerization platforms Exposure to Machine Learning Operations (MLOps) and AI deployment pipelines Familiarity with cloud-based data engineering and big data solutions Experience with AI observability, monitoring, and model evaluation frameworks Recruitment Pro Tip Showcase real-world Generative AI projects that demonstrate RAG implementation, LLM integration, vector database usage, and Agentic AI workflows. Candidates who clearly quantify business impact, such as reduced response time, improved accuracy, increased automation, or production-scale AI deployments, will have a significant advantage during shortlisting and technical interviews. .
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.