Job Summary We are seeking a skilled Software Developer - Generative AI & Python Model Implementation to design, develop, integrate, and deploy AI-powered applications and machine learning models. The ideal candidate will have strong Python development experience, hands-on knowledge of Generative AI/LLMs, and experience taking AI models from experimentation through production. Key Responsibilities Develop and maintain scalable Python applications and AI/ML solutions . Implement and integrate Generative AI models, Large Language Models (LLMs), and AI APIs into production applications. Develop Python-based pipelines for model inference, data processing, evaluation, and automation . Work with frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, or similar AI/ML technologies . Implement techniques such as prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, vector search, and fine-tuning where appropriate. Build APIs and services for AI models using frameworks such as FastAPI or Flask . Optimize models and inference pipelines for performance, scalability, reliability, and cost . Integrate AI solutions with databases, cloud services, enterprise applications, and existing software systems. Develop automated testing and evaluation frameworks to assess model accuracy, quality, latency, and reliability. Collaborate with Data Scientists, ML Engineers, Software Engineers, Product Managers, and other stakeholders. Troubleshoot model, application, integration, and production issues. Follow software engineering best practices, including Git, CI/CD, code reviews, documentation, and automated testing . Required Qualifications Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field. 3+ years of software development experience , preferably with Python. Strong proficiency in Python programming, object-oriented programming, APIs, and software development principles . Hands-on experience implementing machine learning or Generative AI models . Understanding of LLMs, transformers, embeddings, vector databases, and AI inference . Experience with at least one ML framework such as PyTorch or TensorFlow . Experience with REST APIs and microservices . Familiarity with Git, CI/CD, testing, debugging, and production software development. Experience working with relational and/or NoSQL databases. Preferred Qualifications Experience with OpenAI, Anthropic, Google Gemini, Azure OpenAI, or other foundation-model APIs . Experience implementing RAG applications and agentic AI workflows . Experience with vector databases such as Pinecone, Weaviate, Milvus, or FAISS . Experience with cloud platforms such as AWS, Azure, or Google Cloud . Knowledge of Docker, Kubernetes, and cloud-based model deployment . Experience with model monitoring, observability, and AI evaluation. Familiarity with MLOps and LLMOps practices. Experience with fine-tuning, LoRA/PEFT, quantization, or model optimization