Software Developer – Generative AI & Python Model Implementation

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