Highlights
Hands-on coding, GCP services expertise, learning new AI patterns
Description
Job Summary
pWe are seeking an early-career engineer to join our dynamic team, contributing to the development and testing of GenAI and agentic AI components on Google Cloud Platform using Vertex AI and ADK frameworks. This role involves hands-on coding, implementing basic workflows, building agent tools, and integrating with GCP services.
Responsibilities
- Implement basic GenAI workflows: prompt engineering, embeddings, simple RAG pipelines
- Build and integrate agent tools and simple planners using ADK framework
- Work with GCP services: Vertex AI, BigQuery, Cloud Storage, Pub/Sub, Cloud Run
- Write clean, documented code with unit tests
- Participate in code reviews and improve quality based on feedback
- Ensure basic observability through logs, error handling, and retries
Required Skills
- Prompt engineering
- Data embeddings
- RAG pipelines
- GCP services (Vertex AI)
- Python coding
Required Skills Explained
- GenAI Basics: Prompt engineering, embeddings, and simple RAG concepts.
- Agentic AI Basics: Agent loops, tool integration, memory fundamentals.
- GCP Services: Proficiency with Vertex AI, BigQuery, Cloud Storage, Pub/Sub.
- Coding: Strong Python skills and familiarity with APIs and SDKs.
Who is this for
pThis role is ideal for individuals with a passion for GenAI and agentic AI, looking to gain hands-on experience in cloud platforms like Google Cloud. You should have a keen interest in learning new technologies and collaborating within a team environment.
Why This Job is a Good Opportunity
ulliHands-on experience in building GenAI workflows on cutting-edge technology platforms like Google Cloud Platform (GCP).liOpportunity to learn best practices and contribute to innovative AI projects.liCollaborative environment with senior engineers for guidance and mentorship.liPotential for career growth in the rapidly evolving field of GenAI and agentic AI.
Interview Preparation Tips
- Understand GCP services such as Vertex AI, BigQuery, Cloud Storage, Pub/Sub deeply.
- Practice coding problems related to prompt engineering, embeddings, and RAG pipelines in Python.
- Be familiar with writing clean code and performing unit tests.
- Study GenAI and agentic AI principles and their practical applications.
Career Growth in This Role
pIn this role, you will gain extensive experience in GenAI and agentic AI development on GCP. The hands-on nature of the work allows for rapid skill acquisition, making it an excellent stepping stone towards becoming a senior engineer or team lead.pAs you progress, you can explore more complex projects and take on leadership roles within your team, driving innovation and contributing to the success of larger-scale AI initiatives.
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Skills
Frequently Asked Questions
What are the required technical competencies?Candidates should have basic knowledge of GenAI, agentic AI, GCP services, and proficiency in Python.
How much experience is needed for this role?0-3 years of experience in software/data engineering or ML development is preferred.
What kind of collaboration will I be involved in?You will work closely with senior engineers, attend design discussions, and contribute to documentation.
