AI/ML Architect

• *Key Responsibilities**

• *AI/ML Architecture**

Design and implement scalable AI/ML architectures for enterprise applications.

Lead end\-to\-end AI solution delivery from data pipelines to deployment and monitoring.

Build reusable AI frameworks and accelerators.

• *Generative AI \& Agentic AI**

Develop and architect LLM\-based applications.

Design and implement RAG solutions using vector databases and semantic search.

Build AI agents, tool\-calling workflows, multi\-agent systems, and MCP integrations.

Develop conversational assistants, coding assistants, automation agents, and enterprise copilots.

• *Machine Learning Solutions**

Recommendation Systems

Demand Forecasting

Price Prediction

Customer Segmentation

Fraud Detection

Predictive Analytics

Search Relevance \& Ranking

Behavioral Analytics

Optimization Problems

• *Cloud \& MLOps**

Lead AI implementations on GCP using Vertex AI, BigQuery, GKE, Cloud Run, Pub/Sub, Dataflow, and Vector Search.

Establish MLOps best practices including model monitoring, experiment tracking, feature stores, CI/CD, drift detection, and automated retraining.

Deploy scalable AI services using FastAPI, Docker, Kubernetes, and Microservices.

• *Programming \& ML**

Python

NumPy, Pandas, Polars

Scikit\-learn, XGBoost

TensorFlow, PyTorch

• *Generative AI**

Large Language Models (LLMs)

RAG Architecture

Prompt Engineering

Embedding Models

Semantic \& Hybrid Search

AI Agents \& Tool Calling

MCP Integrations

• *Frameworks**

LangChain

LangGraph

LlamaIndex

CrewAI

AutoGen

• *Vector Databases**

Pinecone

Weaviate

FAISS

Milvus

Elasticsearch

Vertex AI Vector Search

• *Cloud \& Infrastructure**

Google Cloud Platform (GCP)

Docker

Kubernetes

GKE

Serverless \& Event\-Driven Architectures

• *Preferred Experience**

Retail, eCommerce, Financial Services, Analytics, Customer Experience, or Enterprise Automation domains.

Experience with Vertex AI Search, Google Commerce Search, Dialogflow CX, OR\-Tools.

Knowledge of Responsible AI and Enterprise AI Governance.

• *What You’ll Drive**

Enterprise AI Strategy \& Roadmap

Scalable AI/ML Platforms

Generative AI Adoption

Customer Personalization \& Automation

AI Engineering and MLOps Best Practices

• *Job Information**
• ------------------

• *Work Experience**
• ------------------

8–10 Years

• *Salary**
• ---------

Best in industry

• *Start Date**
• -------------

Immediate

• *Location**
• -----------

Bangalore, Kadubeesanahalli

• *Qualification**
• ----------------

8–10 years of experience in AI/ML, Data Science, AI Engineering, or related domains.

Proven experience delivering production\-grade AI solutions.