Software Engineer

14 hours ago

India Innova ESI Full time

Must Have Skills: Python Good to have : Generative AI Locations: Chennai/Pune Detailed JD : Position Summary: We seek an experienced Software Engineer with 7+ years of hands-on expertise in Python development and Generative AI technologies. The ideal candidate will design, develop, and deploy RESTful APIs and end-to-end GenAI solutions, driving innovation through experimentation in Jupyter notebooks, robust API development, and advanced prompt engineering across leading LLM platforms. Key Responsibilities: • Develop and maintain REST APIs using Python frameworks such as FastAPI, Flask, or Django REST Framework • Conduct prototyping and experimentation in Jupyter notebooks utilizing ML libraries including scikit-learn, TensorFlow, and PyTorch • Architect and productionize Generative AI pipelines and workflows • Design and optimize prompts, prompt templates, and chain-of-thought strategies for large language models (OpenAI, Anthropic, Hugging Face, etc.) • Integrate vector databases and implement retrieval-augmented generation (RAG) and embedding-based solutions • Containerize applications using Docker and manage deployments via Kubernetes or similar orchestration platforms • Build and maintain CI/CD pipelines for both code and model artifacts using tools like GitLab CI/CD, GitHub Actions, or Cloud Build • Monitor system performance, cost efficiency, accuracy, and ethical compliance; iterate on model evaluation metrics accordingly • Mentor junior engineers on Python best practices, software design principles, and Generative AI methodologies Required Qualifications: • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline • Minimum 7 years of professional experience in Python software development • Strong expertise in REST API design and development with FastAPI, Flask, or Django REST Framework • Extensive experience using Jupyter notebooks for data exploration, prototyping, and model training • Proficient with core machine learning libraries such as scikit-learn, TensorFlow, or PyTorch • Demonstrated experience in prompt engineering and working with multiple large language model providers • Solid understanding of vector embeddings, similarity search, and retrieval-augmented generation architectures • Hands-on experience with Docker containerization and orchestration platforms like Kubernetes, Cloud Run, or ECS • Proven track record in productionizing ML/AI systems including logging, tracing, metrics, and automated rollback mechanisms

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