- Company Name
- Logic Hire Solutions LTD
- Job Title
- Senior GCP AI Cloud Engineer
- Job Description
-
**Job Title:** Senior GCP AI Cloud Engineer
**Role Summary:**
Seasoned engineer responsible for designing, building, and scaling generative AI solutions on Google Cloud Platform. Leads architecture of Vertex AI‑based applications, implements end‑to‑end AI pipelines, and ensures production‑grade reliability, security, and cost efficiency.
**Expactations:**
- 10+ years of software/AI engineering experience, with deep hands‑on expertise in GCP AI/ML services.
- Proven ability to translate complex product requirements into scalable, production‑ready systems.
- Strong leadership: mentor junior staff, collaborate with cross‑functional teams, and provide accurate technical estimates.
**Key Responsibilities:**
- Architect and develop generative AI applications using Vertex AI, Gemini models, and LLM frameworks (LangChain, Vertex AI Agent Builder).
- Build RAG pipelines integrating Vertex AI Search, vector databases, and conversational AI components.
- Design data and infrastructure pipelines leveraging Cloud Storage, BigQuery, Dataflow/Dataproc, Cloud Functions, Cloud Run, and Pub/Sub.
- Conduct rapid prototyping, model benchmarking, and evaluation with Vertex AI Model Garden and Evaluation tools.
- Implement MLOps practices via Vertex AI Pipelines, ML Metadata, Model Monitoring, and CI/CD (Cloud Build, Git).
- Manage GCP resources as code using Terraform; enforce security with IAM, Cloud KMS, DLP, and VPC Service Controls.
**Required Skills:**
- **GCP AI/ML:** Vertex AI (training, prediction, pipelines, Feature Store, Model Registry); Gemini model integration.
- **LLM & Agents:** Experience building agents with LangChain or Vertex AI Agent Builder.
- **Vector Search:** Working knowledge of Vertex AI Vector Search, Pinecone, or Chroma.
- **Core GCP Services:** Cloud Storage, BigQuery, Cloud Functions, Cloud Run, Pub/Sub, IAM.
- **Programming:** Expert in Python; proficient in PySpark or Java (optional).
- **Infrastructure as Code:** Terraform for GCP resource provisioning.
- **MLOps & Security:** Model versioning, monitoring, IAM, Cloud KMS, VPC Service Controls.
- **Additional:** Familiarity with AI‑assisted development tools (e.g., Cursor); AWS AI/ML services a plus.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
- Relevant certifications such as Google Professional Cloud Architect, Google Professional Machine Learning Engineer, or equivalent are strongly preferred.
San francisco, United states
Hybrid
Senior
12-11-2025