Cloud AI Architect - GCP

Cloud AI Architect

Must-Have Qualifications:

• GCP ML & Data Expertise:

  Deep experience with GCP's data and ML ecosystem, including

  BigQuery, Vertex AI, Dataflow/Cloud Composer

  , and robust data governance.

• ML Solution Architecture:

  Proven ability to design end-to-end ML solutions, applying

  MLOps principles

  for training, deployment, and monitoring.

• Backend Development (Python):

  Expert in Python, deploying production-grade

  REST APIs

  using frameworks like FastAPI, Flask, or Django.

• LLM Integration:

  Hands-on experience integrating and deploying

  Large Language Models (LLMs)

  , including prompt engineering.

• API Design:

  Strong knowledge of designing secure and performant

  RESTful APIs

  .

• Database Proficiency:

  Experience with

  RDBMS

  (PostgreSQL, MySQL) and

  Vector Databases

  (e.g., MongoDB, Pinecone), including schema design and optimization.

• Cloud Deployment:

  Experience deploying backend services and ML models on cloud platforms, primarily

  GCP

  .

• Architectural & Communication Skills:

  Ability to translate business needs into technical designs and effectively communicate with stakeholders.

Good-to-Have Qualifications:

• Container Orchestration:

  Experience with

  Kubernetes (GKE)

  .

• CI/CD & DevOps:

  Familiarity with

  CI/CD pipelines

  and Infrastructure as Code (e.g., Terraform).

• Monitoring & Logging:

  Experience with cloud-native monitoring for ML systems.

• Streaming Data:

  Experience with real-time data processing (e.g., Pub/Sub).

• GCP Certifications:

  Professional Cloud Architect or ML Engineer.