Role Overview:

We are seeking a highly skilled Agentic AI / GenAI Engineer (Data Scientist) to design, develop, and deploy production-grade AI systems. The ideal candidate will have strong expertise in building LLM-powered applications, implementing Retrieval-Augmented Generation (RAG), and deploying scalable AI solutions on cloud platforms such as Google Cloud.

Key Responsibilities:

- Design and build scalable AI/ML solutions using LLMs and GenAI frameworks

- Develop APIs and backend services using Python (FastAPI/Flask)

- Implement RAG architectures including ingestion, chunking, embeddings, retrieval, and evaluation

- Work on prompt engineering, tool/function calling, and structured outputs

- Deploy and monitor AI models using MLOps/LLMOps practices

- Ensure security, governance, and compliance (PII handling, prompt injection prevention, data leakage control)

- Build production-ready systems and real-world AI applications

- Collaborate with cross-functional teams for solution design and delivery

Core Technical Skills:

- Strong programming skills in Python

- Experience with FastAPI, REST APIs, async processing

- Hands-on experience in LLM application development

- Strong understanding of embeddings, vector search, prompt design, evaluation, and hallucination control

- Experience in RAG implementation using vector databases (Pinecone, Weaviate, FAISS, Chroma, pgvector)

- Knowledge of LLM security & guardrails

Cloud & Platform Skills (GCP MUST):

- Experience with Vertex AI / Gemini or equivalent platforms

- Experience in deployment using Cloud Run / GKE / similar cloud services

- Exposure to evaluation frameworks such as RAGAS, Evals, custom evaluation pipelines

Agent Frameworks:

- Experience with LangChain, LlamaIndex, Semantic Kernel, CrewAI, or AutoGen

Good to Have:

- Google Agent Development Kit (ADK), Gemini Enterprise / Agent Engine

- Model monitoring & observability tools, multi-agent system architecture, human-in-the-loop workflows, knowledge graph or enterprise search integration

Candidate Profile:

- Strong problem-solving and analytical mindset

- Ability to build end-to-end AI solutions from prototype to production

- Experience working in agile environments

- Excellent communication and collaboration skills