Job Description :

Job Summary :

We are seeking a highly skilled Cloud AI Engineer with strong Cloud and Data Engineering capabilities to design, build, and deploy intelligent AI agents and end-to-end AI solutions.

The ideal candidate bridges the gap between AI research, data engineering, and full-stack software development. You should possess deep expertise in Vertex AI, GCP ADK, modern AI orchestration frameworks, and cloud-native data services.

Beyond building systems, you must have hands-on experience in advanced AI optimizationsincluding prompt engineering, context engineering, and harness engineering.

Experience Required :

5+ Years of total IT experience (with a minimum of 2+ years dedicated to Google Cloud, Machine Learning, and AI)

Job Location : PAN India

Work Mode : Hybrid

Key Responsibilities :

1. AI & Agentic Engineering :

- Multi-Agent Design : Design, develop, and orchestrate complex Agentic AI applications and multi-agent workflows on GCP.

- Core AI Stack : Build and deploy scalable AI solutions leveraging Vertex AI and GCP ADK (Agent Development Kit).

- Advanced LLM Techniques : Implement advanced Prompt Engineering, Context Engineering, and Retrieval-Augmented Generation (RAG) workflows.

- Testing & Evaluation : Design robust evaluation frameworks using Harness Engineering principles to benchmark agent performance, guardrails, and accuracy.

2. Cloud Integration :

- End-to-End Delivery : Develop full-stack AI applications, seamlessly integrating backend services, secure APIs (RESTful/gRPC), and responsive user interfaces.

- Scalable Infrastructure : Design and maintain scalable, secure, and production-grade AI systems utilizing GCP cloud-native architectures.

- DevOps/MLOps : Manage code repositories, implement CI/CD pipelines, and oversee the DevOps lifecycle for continuous integration and deployment of AI models and applications.

3. Data Engineering & Governance :

- Data Pipelines : Work closely with BigQuery, Dataproc, and Dataplex to ingest, process, and analyze massive datasets required for AI context and training.

- Data Governance : Utilize Dataplex for data lineage, quality control, and governance across the AI data lifecycle.

Required Skills & Qualifications :

Technical Skills :

- GCP & AI Services : Deep experience with Google Cloud Platform, Vertex AI, and GCP ADK.

- Programming : Expert proficiency in Python.

- Agentic AI Ecosystem : Proven experience with AI agents, multi-agent orchestration (e.g., LangChain, CrewAI, AutoGen), and LLM APIs. Mastery of GenAI concepts, Prompt Engineering, RAG workflows, and API integrations.

- Data & Storage : Hands-on knowledge of BigQuery, Dataproc, Dataplex, and Vector Databases (e.g., Vertex AI Vector Search, Pinecone, Chroma).

- DevOps & Tools : Strong command of Git, CI/CD pipelines, and Docker/Kubernetes containerization.