Agentic AI / GenAI Engineer (Data Scientist)

Location : Remote

Experience :

6+ years in AI/ML/Data Science/Software Engineering, including at least 3 years of hands-on experience in Generative AI, LLMs, RAG systems, or conversational AI.

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

Mandatory Skills :

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:

1. Embeddings & vector search

2. Prompt design & evaluation

3. Hallucination control techniques

- Experience in RAG implementation using vector databases

- Knowledge of LLM security & guardrails

Cloud & Platform Skills (GCP MUST):

- Experience with Vertex AI / Gemini or equivalent platforms

- Knowledge of vector databases such as:

1. Pinecone, Weaviate, FAISS, Chroma, pgvector

- Experience in deployment using:

1. Cloud Run / GKE / similar cloud services

- Exposure to evaluation frameworks such as:

1. RAGAS, Evals, custom evaluation pipelines

Agent Frameworks :

- Experience with any of the following :

1. LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen

Good to Have (Trainable) :

- 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