GCP AI Engineer

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We are looking for a Senior AI Engineer to build and scale AI-powered applications using Python and Google Cloud Platform. This role focuses on developing backend systems, APIs, and GenAI solutions such as RAG pipelines and AI agents, with a strong emphasis on production readiness and real-world impact.

Key Responsibilities

• 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.

Required Skills & Qualifications

• 58 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.

Good to Have

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

Tech Stack

• Languages & Frameworks: Python, FastAPI, Django.
• Cloud Platform: Google Cloud Platform (Vertex AI, Cloud Run, BigQuery, Cloud Storage, Dataflow, Cloud Composer).
• GenAI: LLMs, Prompt Engineering, RAG, AI Agents.
• Vector Databases: Vertex AI Matching Engine, Pinecone, FAISS.
• Tools & Platforms: GitHub, Jira.
• Frameworks: Google ADK, Lang Chain (or equivalent).le & responsibilities

Preferred candidate profile