We are looking for a Senior AI Engineer to build production-ready GenAI, RAG, and agentic AI solutions across GCP and Azure. The role combines hands-on development, solution design, cloud deployment, and technical mentoring.

Responsibilities :

- Build RAG, autonomous-agent, and multi-agent solutions using LangGraph, LangChain, MCP, and prompt engineering.

- Develop enterprise AI workflows with n8n, Python Code Nodes, APIs, databases, and external systems.

- Work with Gemini and Vertex AI, including Agent Builder, Model Garden, and Vertex AI Search and Conversation.

- Perform data cleansing, chunking, embeddings, vector search, and CDC-based real-time data synchronization.

- Develop and deploy AI services using Python, FastAPI, Docker, and Kubernetes/GKE.

- Fine-tune LLMs/SLMs such as Gemma using PEFT, LoRA/QLoRA.

- Evaluate models for quality, performance, latency, and cost.

- Build AI interfaces using Gradio/Streamlit.

- Support CI/CD, MLOps/LLMOps, monitoring, and production deployments.

- Collaborate with engineering and business teams and mentor junior AI/ML engineers.

Requirements :

- 6+ years of relevant AI/ML engineering experience.

- Strong Python with PyTorch, TensorFlow, or Scikit-learn.

- GCP and Azure experience with enterprise AI workloads.

- Vertex AI, Gemini API, Vertex AI Pipelines, Gemini Code Assist.

- LangGraph, LangChain, MCP, RAG, Agentic AI.

- n8n, FastAPI, Docker, Kubernetes/GKE.

- Azure DevOps, Argo Workflows, CI/CD, MLOps/LLMOps.

- PEFT, LoRA/QLoRA, model evaluation, and optimization.

- Experience with APIs, databases, vector stores, and CDC.

- Strong communication, problem-solving, and stakeholder management skills.

- Preferred : Relevant AI/ML certifications and experience working on large-scale production AI solutions.