About the job :

Job purpose :

- Design & implement the best-engineered technical solutions using the latest technologies and tools.

Who You Are :

- Lead Python development efforts for GenAI and data engineering projects from architecture to deployment.

- Build and optimize LLM-powered pipelines, APIs, and services using OpenAI, Hugging Face, or similar frameworks.

- Architect and implement scalable data pipelines, transformation logic, and feature engineering for AI models.

- Collaborate with ML/AI scientists, data engineers, and product teams to deliver end-to-end GenAI solutions.

- Drive the integration of LLMs into real-time applications (e.g., chatbots, summarizers, copilots).

- Design and maintain efficient, reusable, and reliable Python code using modern frameworks (FastAPI, Django).

- Ensure high code quality through unit testing, code reviews, and adherence to best practices.

- Optimize performance, cost, and scalability of AI-powered backend systems in cloud-native environments.

- Provide technical guidance and mentorship to junior engineers.

What will excite us :

- 5+ years of professional experience in Python backend development.

- 2+ years of experience working with GenAI / LLMs (OpenAI, Hugging Face, LangChain, etc.)

- Hands-on experience with FastAPI, Django, or Flask for scalable API development.

- Strong experience in data engineering : ETL pipelines, data wrangling, feature engineering, and processing large datasets.

- Experience working with Vector Databases (e.g., Pinecone, Weaviate, FAISS) and embedding models.

- Solid grasp of asynchronous programming, RESTful API design, and microservices.

- Proficiency with SQL/NoSQL databases, data lakes, and cloud platforms (AWS/GCP/Azure).

- Familiarity with CI/CD pipelines, Docker, and container orchestration (Kubernetes is a plus).

- Excellent communication and leadership skills with experience mentoring teams or leading projects.

What will excite you :

- Experience with LangChain, LLMOps, or RAG (Retrieval-Augmented Generation) systems.

- Exposure to MLOps tools like MLflow, Kubeflow, or Vertex AI.

- Knowledge of data governance, privacy, and compliance in AI applications.

- Contributions to open-source projects in Python, AI/ML, or data engineering domains.

Work location : Ahmedabad (Work from Office)