1. Gen AI / Python AI Engineer

Position

Gen AI / Python AI Engineer

Job Summary

We are looking for a skilled Gen AI / Python AI Engineer with strong experience in developing, implementing, and deploying AI-driven solutions. The candidate will be responsible for working with Generative AI technologies, Python-based AI applications, machine learning models, and scalable AI/ML systems.

The ideal candidate should have hands-on experience in developing AI solutions and integrating AI models into production environments while ensuring performance, scalability, reliability, and maintainability.

2. Key Responsibilities

- Design, develop, and deploy Generative AI solutions using Python.
- Develop and integrate AI/ML models into applications and production systems.

- Work on model development, training, fine-tuning, optimization, and evaluation.
- Build scalable and reliable Python-based AI applications and services.

- Integrate LLMs and Generative AI models with business applications.
- Develop APIs and services for AI/ML model integration.
- Work with teams to deliver end-to-end AI solutions, from development to production deployment.

- Optimize AI applications for performance, scalability, latency, and cost.
- Troubleshoot and improve AI/ML systems in production.
- Follow best practices for code quality, testing, deployment, monitoring, and reliability.

- Required Skills
- Solid programming experience in Python.
- Hands-on experience with Generative AI / LLMs.
- Good understanding of AI/ML concepts and model development.





- Experience with machine learning/deep learning frameworks.
- Understanding of model deployment and integration.

- Experience building AI-powered applications and APIs.
- Knowledge of REST APIs, FastAPI/Flask, or similar frameworks.
- Understanding of production AI systems and scalable architectures.

- Good problem-solving and analytical skills.

- Preferred GenAI Skills Knowledge or hands-on experience with the following would be beneficial:

- Large Language Models (LLMs)

- Prompt Engineering
- RAG (Retrieval-Augmented Generation)

- Embeddings

- Vector databases

- LangChain / LlamaIndex
- OpenAI or other LLM APIs
- Fine-tuning / model customization
- AI agents and tool/function calling

- LLM evaluation and monitoring
- Deployment & Production The candidate should understand how to take an AI solution from development to production, including:

- API development

- Docker/containerization

- Cloud deployment

- Model serving

- Logging and monitoring

- Performance optimization

- Scalability

- Security

- CI/CD basics
- Overall Requirement The main expectation is that the candidate should be able to develop a Generative AI solution using Python, integrate it into an application, and deploy it as a reliable production-ready service. Interview focus: Based on this JD, I would prepare especially for Python + GenAI/LLM + RAG + ML fundamentals + API development + deployment, with practical project-based questions.

📌 Gen AI / Python AI Engineer (Bengaluru)
🏢 Alike Thoughts
📍 Bengaluru