AI Engineer TSG

The AI Engineer TSG will design and develop scalable backend services and APIs while building and deploying advanced Generative AI applications. The role focuses on architecting end-to-end solutions on Google Cloud Platform (GCP) and integrating LLMs into production environments.

Responsibilities

• Design and develop scalable backend services and APIs using Python (FastAPI/Django).
• Build and deploy GenAI applications, including RAG pipelines, AI agents, and LLM integrations.
• Architect end-to-end solutions on GCP, covering data ingestion, processing, model integration, and deployment.
• Deploy and manage services using Cloud Run, Vertex AI, and other GCP components.
• Implement engineering best practices including CI/CD, logging, monitoring, and performance optimization.
• Collaborate with cross-functional teams and mentor junior engineers.

Required Qualifications

• 5–8 years of experience in software engineering with strong expertise in Python.
• Hands-on experience with backend frameworks (FastAPI, Django) and RESTful APIs.
• Strong experience with GCP (Vertex AI, Cloud Run, BigQuery, Cloud Storage, Dataflow, PostgreSQL).
• Experience with AI agents, Google ADK, and Model Context Protocol (MCP).
• Proficiency in GenAI orchestration frameworks like LangChain.
• Experience working with unstructured data and vector databases.
• Familiarity with Agile workflows and version control (GitHub).
• Educational background: BE (IT) or MTech.

Preferred Qualifications

• Understanding of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with MLOps practices and model lifecycle management.