AI Engineer TSG

• Design and develop scalable backend services and APIs using Python (Fast API / 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 manage work through Jira.

• Use GitHub for version control, code reviews, and maintain clean, production-grade code.

• Mentor junior engineers and contribute to technical design and standards.

Qualifications

• 5–8 years of experience in software engineering with strong expertise in Python.

• Hands-on experience with backend frameworks such as Fast API and Django.

• Experience building RESTful APIs and scalable microservices.

• Strong experience with Google Cloud Platform (Vertex AI, Cloud Run, BigQuery, Cloud Storage, Dataflow, PostgreSQL).

• Experience with AI agents, Google ADK, and Model Context Protocol (MCP).

• Exposure GenAI orchestration frameworks (LangChain or similar).

• Experience working with unstructured data (PDFs, documents, engineering data).

• Knowledge of cloud cost optimization and system performance tuning.

• Experience working with LLMs and GenAI use cases (prompting, integrations, APIs).

• Hands-on experience with RAG pipelines and vector databases.

• Experience with GitHub (branching, pull requests, code reviews).

  • Familiarity with Agile workflows and tools like Jira.