Python Gen AI Engineer (RARR Job 5806)

We are looking for a skilled Python & Generative AI Engineer with strong experience in prompt engineering and FastAPI-based application development. The ideal candidate will design, develop, and deploy AI-driven solutions, integrate LLM capabilities into applications, and build scalable APIs to support GenAI workflows.

Key Responsibilities:

• Develop and maintain backend services and APIs using FastAPI.

• Build, integrate, and fine-tune Generative AI models (OpenAI, Azure OpenAI, Anthropic, Llama, etc.).

• Design, test, and optimize prompts, chains, and workflows for LLM-based applications.

• Develop reusable components for RAG (Retrieval-Augmented Generation), embeddings, vector databases, and knowledge pipelines.

• Implement automation scripts and utilities using Python.

• Work with unstructured and structured data to build AI-driven features.

• Optimize model performance, latency, and quality of outputs.

• Ensure API reliability, authentication, and production-grade deployment.

• Collaborate with stakeholders to convert business requirements into GenAI use cases.

• Maintain high-quality documentation, testing, and CI/CD practices.

Required Skills & Experience:

• 3–7 years of hands-on experience in Python development.

• Strong experience in building RESTful APIs with FastAPI.

• Hands-on experience with LLMs, Generative AI, and prompt engineering.

• Familiarity with vector databases (FAISS, Pinecone, Chroma, Weaviate, etc.).

• Experience with RAG pipelines, embeddings, and model integrations.

• Strong understanding of OpenAI / Azure OpenAI / Hugging Face model APIs.

• Experience working with Docker, Git, and cloud platforms (AWS/Azure/GCP).

• Good understanding of ML fundamentals, data preprocessing, and model deployment.

• Ability to write clean, efficient, and well-documented Python code.

Good to Have:

• Experience with LangChain, LlamaIndex, or similar orchestration frameworks.

• Knowledge of Kafka, microservices, or event-driven architecture.

• Experience with MLOps tools (MLflow, Airflow, Kubernetes).

• Exposure to front-end frameworks (React/Angular) is a plus.

• Experience with fine-tuning LLMs or custom model training.

Soft Skills:

• Strong analytical and problem-solving skills.

• Excellent communication and stakeholder management.

• Ability to work in an agile, fast-paced environment.

• Proactive mindset with ownership of end-to-end solutions.